Business Analytics Blog Posts

Over the years, Business Analysis has emerged as a core business practice in the enterprise and IT sectors. It pertains to understanding the changing business needs, evaluating the impact of such changes, identifying and analyzing the requirements and documenting the same, and facilitating communication among all the stakeholders involved. This is essentially what Business Analysts do.  Business Analysts act as a bridge between an organization’s IT and Business domains and contribute actively to its profitability and sustainability. Since traditional methods no longer suffice for catering to the dynamic needs of the complex business environment, Business Analysis comes to the rescue. With their expertise, agility, and drive for innovation, Business Analysts guide enterprises in improving their processes and quality of products/services while ensuring the timely dispatch of client deliverables. Check out our business analytics free online courses What does it take to be a Business Analyst? The fundamental job responsibility of a Business Analyst is to elicit, analyze, and validate the change requirements for business processes, information systems, and policies and to communicate them with all stakeholders. Entailing all these critical responsibilities, there is ample business analyst scope in India. They interact with both the business partners and users to understand how data-driven changes to business processes, products/services, and software/hardware can enhance efficiencies and add value to the organization.  They work in close collaboration with the IT and Financial reporting teams to design and implement new business models to support the proposed business decisions and to establish initiatives/policies to improve productivity and to optimize costs.  They identify an organisation’s business goals and problems and create lucrative solutions. Their excellent problem-solving skills suggest a high business analyst average salary. They understand and gather business requirements from stakeholders and clients. They proactively offer feedback on a software application’s design and employ the innovative features that a business requires. This is another reason behind accelerating business analyst salary in leading organisations. They assess the functional and non-functional requirements in a corporate. They organise regular meetings with clients and stakeholders to discuss business concerns and derive solutions. The scope of business analyst in India is increasing because they are experts at ensuring that business solutions are aligned with the client’s requirements. Also, they validate a project’s status through user acceptance testing. The business analyst average salary is admirable in many small and large-scale organisations. This is because they can document and build data visualisations to deliver all the project outcomes. They analyze what’s financially and technologically feasible for the company.  Read: What is business analytics – Its Career scope, Salary & Job Roles. According to Robert Half Technology, the job description of a Business Analyst includes: Creating detailed business analysis and drafting problems, opportunities, and solutions for a company. Defining business requirements and reporting them back to stakeholders. Budgeting and forecasting. Planning and monitoring. Variance analysis. Pricing. Reporting.  Although a Business Analyst need not have an IT background, he/she must have a basic understanding of how IT systems function. What they need is a strong and in-depth understanding of the business domain. Prior experience in forecasting, budgeting, and financial analysis are highly commendable. Apart from this, it is beneficial to be well-versed with the regulatory and reporting requirements. While for entry-level Business Analyst job roles, a bachelor’s degree in Business Administration/Management/Information Technology is enough, mid-level and senior-level positions often demand a master’s degree in business analytics or any other related fields.  Learn best MBA courses from the World’s top Universities. Earn Masters, Executive PGP, or Advanced Certificate Programs to fast-track your career. Business Analyst: Who Are They? Business Analysts are experts holding specialization in the BI or Business Intelligence sector. They operate as an intermediary or link between an organization’s business and IT departments, intending to boost its profitability and viability.   Today, companies pay a good business analyst salary to make improvements to the company’s goods, services, and level of quality using their expertise. Business Analyst: What Do They Do? A business analyst’s main responsibility is communicating with business executives to learn how data-driven decisions might increase organizational effectiveness.  Business analysts evaluate organizational processes, grasp numerous business requirements, and give concepts, suggestions, and reports to help management understand the state of the company.  Ultimately, they implement business ideas that are technically and financially feasible for the organization. But given that the business analyst salary in India is more than the industry standard, they need to take on a lot of roles and responsibilities.  So, now go over each of these professions’ distinct tasks and duties.  Analyze the business procedures to determine the needs  Determine what needs to be improved, then take action.  Analyze the operational procedures to develop optimisation ideas. Keep up with the most recent technological developments.  Automate the business’s current procedures.  Outline and make your suggestions on how to make these systems better.  Share your ideas and ambitions with the company’s various divisions.  Work with the business’s IT department and the clientele.  Gather information and data from different stakeholders to create useful reports.  Maintain resource allocation and cost-effectiveness. Implement updated business procedures.  Becoming a Business Analyst: How To Proceed? The steps listed below must be followed in order to master business analytics and become a business analyst:  Obtain a business-related bachelor’s degree or an MBA.  Obtain analytical job experience and develop your reporting and documentation skills  Get practice using different business analytics tools  Obtain work experience working on numerous projects for your sector  Acquire expertise in Microsoft Word, Excel, Outlook, and other programmes. Business Analyst Salary in India Source The salary of a Business Analyst in India depends upon several factors like company size and reputation, job position, location, education qualifications, and experience. Usually, reputed companies like TCS, Amazon, Accenture, Deloitte, etc., pay higher salaries. Then again candidates hailing from reputed institutes/b-schools earn more than their counterparts. This holds true for work experience as well – the more your experience, the higher will be your market value. Our learners also read: Learn business analytics free! Salary scale – Popular companies in India Tata Consultancy Services (TCS), Accenture, Computer Sciences Corporation (CSC), and Capgemini offer the are some of the top companies with the highest salary packages for Business Analysts. While the average annual salary at Accenture is Rs. 7,04,965, Capgemini and TCS offer around Rs. 7,03,178 and Rs. 696,132 respectively. HCL, Wipro, and CSC fall on the lower end of the salary scale with the average annual salary standing around Rs. 5,21,246, Rs. 5,79,188, and Rs. 6,02,435, respectively.  Source Salary packages of reputed e-commerce platforms like Amazon are also great. In India, the average annual salary of a Business Analyst at Amazon ranges anywhere between Rs. 3,28,484 – 17,83,171, with senior-level roles earning the higher end of the salary scale. Also read: Business analyst career path and professional roles. upGrad’s Exclusive Business Analytics Webinar for you – How upGrad helps for your Business Analytics Career? document.createElement('video'); https://cdn.upgrad.com/blog/alumni-talk-by-monalisha-dash.mp4   Salary scale – Experience Level Generally, the salary packages for entry-level roles remain anywhere between Rs. 3,50,000 – 5,00,000. For instance, the average annual Business Analyst salary (including tips, bonus, and overtime pay) at the entry-level in IT with less than 1-year experience is around Rs 3,59,807. However, the Business Analyst salary for those having 1-4 years of experience can earn an annual compensation of Rs 5,27,712.  Source The salary level increases as experience increases. While a Business Analyst having 5-9 years of industry experience can earn around Rs. 8,30,975, a Senior Business Analyst, with over 15 years of experience, can easily make Rs 12,09,787. Going further, the salary increases up to Rs. 16,54,946. Salary scale – Location Salary packages also differ considerably according to location as well. For instance, Business Analysts in Pune and Bangalore earn around 17.7% and 12.9% more than the national average. Noida (8.2% less), Chennai (5.2% less), and Hyderabad (4.2% less) record the lowest level salaries.  Source Owing to the significant scope of business analyst in India, it is imperative to determine the most influencing factors. One of the most dominating factors that influence business analyst entry level salary is location. Not only do senior business analyst salary in India, but many fresher business analysts possessing exceptional skills can get an admirable salary, for instance, business analyst salary Bangalore is comparatively higher than in any other place. So, the entry level business analyst salary is great for skilled freshers in prime locations. The average business analyst salary Bangalore is Rs.9,00,000 per annum. Moreover, the average additional cash compensation to be added to a business analyst salary in Bangalore is Rs.1,00,000, with a range of Rs.50,000 – Rs.2,57,400. Candidates aiming to obtain higher packages can rely on business analyst salary in Bangalore. Many leading companies on the lookout for business analysts offer outstanding salaries. The companies offering great business analyst salary Pune: 2COMS Consulting Pvt Ltd Ikya Human Capital Solutions Pvt Ltd Zensar Technologies Orange Business Services All these companies carefully recruit business analysts based on skills and experience and ultimately offer the most suitable business analyst salary Pune. The business analyst salary Hyderabad depends on many factors and one of them is the type of employer. List of companies that provide outstanding business analyst salary Hyderabad: Zensar Technologies Clarity Consulting Uber Tech Mahindra Orange Business Services The business analyst salary Chennai significantly relies on the employer profile. List of employers providing excellent business analyst salary Chennai: Ikya Human Capital Solutions Pvt Ltd Zensar Technologies Orange Business Services Tech Mahindra When it comes to business analysts’ remuneration based on location, you must consider business analyst salary Delhi. Here is the list of companies renowned for offering superb business analyst salary Delhi: Top companies for Business Analysts in Delhi Amazon.com Zensar Technologies HCL Technologies Tech Mahindra Orange Business Services Being one of the megacities, the business analyst salary Mumbai must be considered. Names of a few of the prominent companies that provide outstanding business analyst salary Mumbai: Ikya Human Capital Solutions Pvt Ltd 2COMS Consulting Pvt Ltd TrueTech Solutions Zensar Technologies Business Analyst Salary Based on Skills Your skills as a business analyst can vary based on the industry and domain. However, possessing a range of skills yields a good business analytics salary of fresher business analyst salary in India.  Here is a table representing the average business analytics salary in India for people with different skill sets. The amount will vary depending on your region and expertise, but this is the base average compensation for these job roles.  Skills of a Business Analyst Average Salary Per Year Requirement Analysis INR 6,59,932 Microsoft Excel Expert INR 5,57,736 Business Analysis INR 6,31,572 Project Management INR 5,93,715 SQL INR 6,47,341 As you can see, the salary of a business analyst in India will rise in direct proportion to the number of talents you learn. For this reason, it is crucial to improve your IT skills.  Moreover, remember that a fresher business analyst’s salary in India increases progressively as they gain more experience and upgrade their skill sets.  Business Analyst Salary Based on Industry The industry you work in will also have an impact on your business analyst salary so it is essential for you to know business analyst job description salary beforehand. Here is a detailed summary of the annual salaries of salary of business analyst in India you might anticipate. Dependent on the sector you decide to work in.  Industry Average Salary Per Year Financial Services INR 8,10,000 Hardware and Networking INR 7,30,000 IT Consulting and Services INR 7,00,000 Internet INR 8,40,000 Manufacturing INR 7,00,000 Explore our Business Analytics Programs from World's Top Universities Business Analytics Certification Programme Busines Analytics EPGP - LIBA Professional Certificate Program in Data Science and Business Analytics Master of Science in Business Analytics Global Master Certificate in Business Analytics Busines Analytics Certification - upGrad Demand for Business Analysts in India: The business analyst demand in India is high for skilled candidates who can manage their data and predict market opportunities. Generally, small-scale and mid-size companies in India recruit business analysts to make better monetary decisions and optimize cost. So, they provide a deserving business analyst salary who can adopt many roles, including budget management and resource allocation. You can gauge the accelerating business analyst demand in India from the fact that there are many leading firms hiring business analysts in India. These firms are Accenture, Tata Consultancy Services, Amazon, Flipkart, Deloitte, Ernst & Young, etc. Based on surveys carried out by LinkedIn, the average salary of a business analyst annually in India is approx. INR 13.5 lakh with salaries varying from INR 5.3 lakh to 22.1 lakh. India perceives the use of cutting-edge technologies for streamlining business processes. Several firms in India use technologies like machine learning, data analysis, deep learning, artificial intelligence, etc. Moreover, business analysts use data analysis tools to have better forecasts and this is one of the reasons for the extensive business analyst scope in India. The Covid-19 attack has caused a lot of market interruption in India and worldwide. Many firms are finding it difficult to survive and gradually comprehend the requirement for skilled business analysts to predict risks and opportunities. India is a developing country and many businesses are transitioning. The demand for business analysts is accelerating due to the need for data management and forecasting abilities. In addition to analytical jobs, business analysts can do various tasks. They can work as project coordinators, mediators, etc., whenever required. India’s dearth of skilled business analysts has opened doors to diverse job roles. Key Skills Required for Business Analysts: If you are planning to become a business analyst in India, these are the keys skills you must know: 1. Technical Skills: Learning certain key technical skills can promise a decent entry level business analyst salary. Business analysts must know SQL (Structured Query Language), Microsoft Office, Microsoft Visio, etc. In addition, freshers can have a well-paying business analyst entry level salary if they are fluent in software designing and business model designing tools. They also need to collaborate with the IT team and share business objectives with them. 2. Financial Planning Skills: Business analysts must ascertain that all the resources are assigned within the organization’s financial budget. They should also learn how to assist clients in having better commercial decisions. 3. Analytical Skills: They must be well-versed in data analysis and statistics. Usually, they are tasked with managing big data to discern key insights. Moreover, they must have forecasting skills to accelerate their career graph. Employers prioritise analytical skills, which are a must for senior business analyst salary in India. Read our Other Articles Related to Business Analytics What is Business Analytics? Career, Salary & Job Roles Top 7 Career Options in Business Analytics Business Analytics Free Online Course with Certification Business Analytics Vs Data Analytics: Difference Between Business Analytics and Data Analytics Top 7 Best Business Analytics Tools Recommended for every Business Analyst Top 11 Industry Applications of Business Analytics Future Scope of Business Analytics Business Analytics Eligibility or Requirement 8 Business Analytics Tips: Which Helps to Run Business Successfully 4. Problem-Solving Skills: They must possess interpretation skills to understand the risks. One of their major responsibilities is risk identification and management. 5. Communication skills: They must effectively convey stakeholders’ expectations to the employees. Moreover, they need to conduct meetings and brainstorming sessions regularly. So, communication skills are vital. To conclude, Business Analysts have a decent pay scale in India. Companies across both IT and e-commerce sectors pay excellent compensation to deserving candidates who can add value to their organization. Apart from the regular educational qualifications and work experience, having advanced Business Analysis certifications also helps in bagging jobs that offer high-level salaries. If you are keen on upgrading your career with an Executive MBA course, upGrad is offering MBA from Liverpool Business School. The program has been designed to stand at par with the best on-campus Executive MBA programs across the globe. Learn Business Analytics Courses online from the World’s top Universities. Earn Masters, Executive PGP, or Advanced Certificate Programs to fast-track your career.

Business intelligence (BI) tools are applications that collect and interpret massive volumes of unstructured information from internal and external systems such as books, journals, papers, health records, photographs, files, email, video, and other business sources. While not as adaptable as business analytics tools, BI tools collect data and search for relevant information mainly through queries. These technologies also aid in preparing data for analysis, allowing you to build reports, dashboards, and data visualisations.  Employees and managers can use BI tools to effectively leverage data to speed and enhance decision making, increase operational efficiency, uncover new income potentials, detect market trends, provide authentic KPIs, and identify new business prospects. Explore our Business Analytics Programs from World's Top Universities Business Analytics Certification Programme Busines Analytics EPGP - LIBA Professional Certificate Program in Data Science and Business Analytics Master of Science in Business Analytics Global Master Certificate in Business Analytics Busines Analytics Certification - upGrad Business Intelligence Tools: What Are They? Before exploring the top business intelligence tools, let’s learn what these tools actually are. Today, organizations leverage BI tools to gather, process, and analyze large chunks of unstructured and structured data.  Now what are the sources for such data? It may include standard files, social media posts, journals, emails, books, documents, and photographs.  Today, the best BI tools leverage queries to retrieve this data, which can then be shown/displayed as dashboards, charts, graphs, and reports for convenience in use. Whether it’s analytics, performance management, text mining, reporting or predictive analysis, BI tools are capable of handling all such tasks.  But what’s the fuss about collecting and analyzing all this data? Well, employees in organizations can leverage this data to make smarter decisions based on KPIs, market trends, and forecasts.  Why is Business Intelligence essential? Business intelligence solutions analyse raw data utilising seasonal, trend analysis, what-if scenarios, modelling with various data modelling approaches, and similar features. BI offers a wide range of features for producing reports to help you better understand your company data. Business users may generate, examine, and change reports and visualisations both online and offline and in conjunction with other office tools. A business intelligence system provides tools for analysing real-time, up-to-the-second operational data, allowing the company to make swift and educated choices. The system includes dashboards that allow businesses to monitor, measure, and manage company performance in a timely and controllable manner. Business Intelligence solutions include industry-standard scorecards that allow businesses to track essential performance metrics. A BI solution allows you to exchange information with diverse stakeholders both inside and outside your firm. It includes features that enable the same information, including reports, dashboards, and monitoring, to be accessed through a mobile device. Some BI tools provide extensive analytics and visualisation capabilities, allowing for real-time visualisation in various formats and ways and the inclusion of extra functionality. Learn Business Analytics Courses online from the World’s top Universities. Earn Masters, Executive PGP, or Advanced Certificate Programs to fast-track your career. Top Business Intelligence Tools  1. Datapine  Datapine is a business intelligence programme that allows you to link data from many sources and analyse it using advanced capabilities (including predictive analytics and artificial intelligence). With all of your data at your disposal, you can build a sophisticated business dashboard (or multiple), generate standard or customised reports, and add intelligent alerts to be warned of anomalies and goals. The programme caters to expert users, such as data analysts and regular business users. The SQL mode allows analysts to write their queries, while the simple drag-and-drop interface provides a visually intuitive manner of entering numbers and building impressive charts and dashboards simply by utilising effective visual analytics.  2. Zoho Analytics Zoho Analytics is an excellent BI solution for detailed reporting and data analysis. This business intelligence solution supports automated data synchronisation and may be scheduled regularly. Using the integration APIs, you can quickly create a connection. Create relevant reports by blending and merging data from many sources. You may build customised reports and dashboards with a simple editor, allowing you to hone in on the relevant facts. It also has a special comments box in the sharing choices, ideal for cooperation. 3. Domo Domo is a cloud-based platform that focuses on business-user dashboard deployment and usability. It provides business information solutions targeted to specific sectors and functions (such as financial services, health care, manufacturing, and education) (including CEOs, sales, BI professionals and IT workers). CIOs may begin by investigating how it manages data from AWS, Jira, GitHub, or New Relic before exploring how over 500 more connectors might benefit the rest of the company. 4. Microsoft Power BI Users may analyse and display data from local or cloud sources using the Power BI Desktop programme for Windows and then publish their findings to the Power BI platform. Data preparation, visual-based exploration, interactive dashboards, and augmented analytics are available. The free Power BI Desktop version is intended for isolated users; the Pro version, available for a monthly fee, facilitates collaborative analysis by integrating Microsoft Office365, SharePoint, and Teams to limit access to raw data and published results. The Premium tier enables self-service data prep with prebuilt connections to corporate data stored in Microsoft Dynamics 365, Azure SQL Data Warehouse, or third-party sources such as Salesforce for companies willing to go all-in. 5. Oracle Business Intelligence Oracle Business Intelligence is a technology and application portfolio that focuses on offering end-to-end solutions to assist organisations in enhancing their performance and encouraging people to make faster and much more informed mobile-enabled decisions.  They provide a broad range of data management capabilities such as machine learning, artificial intelligence, an integrated array of querying, reporting, and mobile analytics. Oracle’s purpose has been to give organisations tools to successfully manage their data comprehensively and efficiently since its inception in 1977. 6. Qlik Qlik’s objective is to offer everybody in the business access to all of its data, according to corporate data governance regulations, of course. All of that data should be enough to slow down most database engines, but Qlik claims its Associative Engine can associate each item of data with every other piece to make searching for connections faster. Because of the Qlik cognitive engine, the Associative Engine now offers AI and machine learning capabilities that provide context-aware insight recommendations. Qlik Sense, the self-service platform for gaining access to that analytical power, is available in the cloud and on-premises editions. 7. Tibco Spotfire Tibco Spotfire is an AI-powered data visualisation platform for self-service dashboards, interactive visualisation, data preparation, and workflow. To aid in the development of complicated data models, the platform includes machine learning-based data preparation capabilities. It is used in various industries, including finance, energy, manufacturing, consumer packaged products, government, transport and logistics, healthcare, and life sciences. Python support has been included in the most recent version. 8. Microstrategy MicroStrategy is a ‘software and mobility’ platform for enterprise business analytics that focuses on hyperintelligence, federated analytics, and cloud solutions. Their mobile dossiers allow customers to create interactive analytics books that can be viewed on iOS or Android smartphones, with the option to integrate MicroStrategy material into their apps using Xcode or JavaScript. In addition, you can get a sample app, MicroStrategy Mobile, or the Library app, which will allow you to install analytics on the fly. 9. Sap Business Objects SAP Business Objects is a business intelligence application that provides comprehensive reporting, analysis, and interactive data visualisation. The platform strongly emphasises areas like Customer Experience (CX) and CRM, digital supply chain, ERP, and others. What’s particularly appealing about this platform is the self-service, role-based dashboards it provides, which allow users to create their dashboards and apps. SAP is a strong programme designed for all roles (IT, end-users, and management) that provides many features on a single platform.  10. Yellowfin BI Yellowfin BI is a business intelligence tool and “end-to-end” analytics platform that integrates visualisation, machine learning, and collaboration. You may also simply sift through large amounts of data using easy filters (e.g., checkboxes and radio buttons), as well as open dashboards from almost anywhere (due to the tool’s accessibility flexibility) (mobile, webpage, etc.). The wonderful thing about this BI tool is that it allows you to simply take dashboards and visualisations to the next level by employing a no-code/low code development environment. How To Choose The Best Business Intelligence Software? Know What Your Company Needs: First, ask or research the sort of information your organization needs to gather, evaluate, analyze, and deploy for decision-making. Do you need to monitor supply chain operations, financial data, consumer interaction, or sales? You can reduce the possibilities and select a business intelligence solution that supports your objectives by determining your company’s demands.  Make a Budget: The best business intelligence software may be costly, but the price varies from one software to another. However, everything that is costly isn’t necessarily the best fit for us, and the same theory applies to BI tools. You can keep within your means and still receive a product that meets your business objectives by creating a budget.  Evaluate The Accessibility & Simplicity of Use: The best business intelligence solutions are simple to use and intuitive, allowing your staff to have access to information fast. A user-friendly program will allow your staff to focus on data analysis and action instead of training, saving you time and money.  Look For Capabilities Allowing Unique Data Visualization: Data visualization has many advantages, including making difficult-to-understand data understandable and enhancing team communication. Tools for visual business information can facilitate greater insights into trends and patterns, which can enhance decision-making. An excellent solution will also be adaptable to your particular business requirements, offering various features and filters that match your information and preferences.  Compatibility Check With Current Tech Stack: To minimize additional costs, take into account the analytics solution’s compatibility with your current technology infrastructure. An excellent one will be simple to integrate with your existing database management systems and work with the technologies you already have.  So, are you prepared to advance your management of performance and productivity? Use a strong business intelligence solution to help you simplify and streamline your processes and maximize the potential of your staff.  Popular BI Tools On Resume: A Worthwhile Addition!  By learning on your own or while working, you can become acquainted with more than one BI tool. Leading organizations now rely on their use.  So, if it makes value for the position and the field in which you’re making an application, you can gain from adding the most popular BI tools in the skills area of your resume. Also, if a particular BI tool is mentioned in the job description, recruiters may look out for candidates who hold expertise in it. Read our Other Articles Related to Business Analytics What is Business Analytics? Career, Salary & Job Roles Top 7 Career Options in Business Analytics Business Analytics Free Online Course with Certification Business Analytics Vs Data Analytics: Difference Between Business Analytics and Data Analytics Top 7 Best Business Analytics Tools Recommended for every Business Analyst Top 11 Industry Applications of Business Analytics Future Scope of Business Analytics Business Analytics Eligibility or Requirement 8 Business Analytics Tips: Which Helps to Run Business Successfully Conclusion  Artificial intelligence is steadily taking over. With the multiple capabilities that BI tools and business analytics tools have to offer, you stand to gain significant benefits – your data management will become more unified, stable, agile, and predictable.  Wondering where to find the ideal Business Analytics Course? upGrad’s Global Master Certificate in Business Analytics is what you need! This course will help you learn the fundamentals of leveraging data to improve corporate performance, rapid decision-making, and long-term plan formulation. Key Highlights: Interactive discussion boards, quizzes and case studies are regularly conducted The course gives a comprehensive grasp of business analytics and how they can be used to improve performance. This course is 100% online This course will assist you in investigating the most recent industry developments, such as how to exploit geographical data generated by mobile and social media generation and evaluating client lifetime value. Learn how to use essential analytical, modelling, and statistical tools including Tableau, R, and Microsoft Access. Sign up today and grab the chance of learning from the best in the industry!

What Is VBA? Do you know what VBA stands for? VBA full form is Visual Basic for Applications. This simple, but powerful programming language was developed by Microsoft Corp. And now VBA is broadly used with other Microsoft Office applications, for example, MS Word, MS Excel, MS Access, MS PowerPoint, Publisher, etc. This language is utilized in writing programs for the Windows operating system and runs as an internal programming language in Microsoft Office. VBA allows techies to customize applications beyond what is usually available with MS Office for example creating user-defined functions, automating computer processes, and accessing Windows APIs. It also allows users to build solutions to improve those applications’ proficiencies. If you are facing problems in effectively importing your contacts from MS Outlook into an Excel spreadsheet, in repeatedly cleaning up fifty tables in Word or you want a specific document to ask the user for input when it opens then VBA will help you perform all these tasks. You do not have to install Visual Basics on your PC rather installing MS Office will help you to achieve the objectives. A user can use VBA in all available latest office versions, from MS Office 97 to MS Office 2013. Among all Excel VBA is the widely used VBA. Visual Basic Excel is used for Applications in the Context of Excel. You can get a deeper understanding of this concept via Master of Science in Business Analytics from GGU. Check out our free courses related to upskill yourself. How is VBA Used? VBA is a programming language that can be used for a variety of tasks, and it is utilized by various types of users for those tasks. The various organizations that utilize VBA include the following. General Users: Generally, users use Excel and other MS Office programs. The user can utilize the MS Office Suite with VBA language free of cost. VBA is used to create and organize spreadsheets. In addition, it is used in numerous other tasks such as if a user has to automate some Excel features like repetitive tasks, frequent tasks, generating reports, etc then it can be done by using VBA. For this purpose, the user can create a VBA program within Excel to produce format and print monthly sales reports with graphical representations like bar graphs. Computer Professional: Computer professionals can use VBA to perform more complicated tasks that would otherwise require more time and resources. VBA offers some new functions that are not available in Excel such as creating custom add-ins that enhance the application’s functionality, rewriting lengthy lines of code, creating custom languages within Microsoft Office applications, and combining the functions of multiple programs, etc. Corporate Users: The corporate users of various companies use the VBA programming language to automate critical business procedures and internal processes, accounting procedures, minute records, real-time processing of sales orders, complex data calculations, and more. Learn business analytics courses online from the World’s top Universities. Earn Masters, Executive PG Programmer Certification, or Global Master Certification to fast-track your career. Why use Excel VBA Although VBA cannot be used to directly alter the main Excel software, the users can learn to create macros to optimize their time in Excel. Excel macros are created in two ways. By using Macro Recorder: In this technique as soon as the recorder is turned on, Excel will begin to capture every action the user takes and save it as a macro, or “process”. When the user closes the recorder, the macro is saved and can be linked to a button that, when clicked, will repeat the entire process. To use this technique no prior knowledge of VBA is required. Using VBA: This is a robust method where Excel macros can be programmed using VBA. Where to code Excel VBA Within any Office program, press Alt F11 to open the VBA window.  This will open a window with a file structure tree, the coding section that occupies most of the screen in the center. The coding takes place in the coding section. Here, the user can create macros and save them. Once the macro code has been created and saved, it can be attached to certain triggers in the Excel model. The macro can be activated after pressing a certain worksheet button. VBA shortcuts in Excel Some shortcuts that operate while using VBA in Microsoft Excel are listed below. Alt F11: To open the VBA editor Alt F8: To view all macros Alt F4: To exit the VBA Editor and return to Excel F1: To display Help Ctrl space: Autocomplete  Alt F5: To run error handler Alt F6: To swap the last two windows Alt F11: To switch between Excel and the VBA editor F7: To start on the code editor F10: To start the menu bar Home: Starting of line You can apply these shortcuts in a practical background with the help of the Executive PG Program in Business Analytics from LIBA.  What can you do with VBA Finance is fundamentally about handling vast amounts of data, so VBA is omnipresent in the financial services industry. If you work in finance, VBA is probably running within programs you use on a daily basis. By using VBA, you can accomplish the following things. Write Macros: Macros permit all financial professionals like investment bankers, research analysts, salesmen, traders, Accountants, commercial bankers, clerks, and administrators. To compose macros to quickly analyze and modify massive amounts of data. Update Data: VBA in Excel is used to forecast sales and earnings, produce financial ratios, and build and maintain trading, pricing, and risk management models. Conduct a scenario analysis: You can create various scenarios for portfolio management and investment using Visual Basic.  Organize the information: VBA can also be used to create invoices, forms, and charts, analyze scientific data, and manage data displays for budgeting and forecasting. It can also be used to create lists of customers’ names. Be unconventional: Values can be copied and pasted, cell styles for an entire workbook can be changed, and accelerator keys can be pressed using VBA. You can execute very common tasks in an easier and more automated manner.  Prompt Action: You can communicate with users by using VBA.  Acquire the above mentioned expertise with a deep insight into Professional Certificate Program in Data Science and Business Analytics. Enable the Developer Option in Excel On the ribbon, it by default hides the Developer tab. Follow the instructions listed below to customize the ribbon. First right-click on the ribbon and then click on the Customize the Ribbon option. Select the Developer checkbox under Customize the Ribbon. VBA Editor Interface To open the VBA Interface press the shortcut key Alt F11. You can also open it by clicking the Visual Basic on the Developer tab. Create an Excel Macro using a Command Button To create an Excel Macro using a command button follow the below steps. Go to the Developer tab, then click on Insert, then ActiveX controls and then select the Command button.   Developer tab > Insert > ActiveX Controls > Command button Select and drag the command button on your worksheet. Right-click on the command buttons and select the View Code option.  Add the VBA code excel that is given below. Private Sub CommandButton1_Click() Range(“A1”).Value= “Learnbasics” End sub Close the VBA editor and click on the command button on the worksheet. Create an Input Box The following steps are to be followed to create an input box in Excel that will prompt a message on your worksheet. The Syntax used to create an input box is:  InputBox(prompt[,title][,default][,xpos][,ypos][,helpfile,context]) To add the InputBox to the command button first declare the variable name and keep the type variant to hold any type of value. Write the following code to show the input box. Private Sub CommandButton1_Click() Dim Learnbasics As Variant Learnbasics = InputBox(“Enter your message”) Range(“A1”).Value= “Learnbasics” End sub Now click on the command button to get a prompt asking you to enter your message. Enter your message and click OK. It will be entered and shown as input on cell A1. Variables, Constant, and Operators in VBA Variable:The data types that are used to store values are known as variables. During program execution, we can modify the variables. Syntax: Dim <<Name_of_variable >> As <<Type_of_variable>> VBA data types can be classified into two categories.  Numeric Data Types: These data types consist of byte, integer, long, single, double, currency, and decimal.  Non-Numeric Data Types: These data types consist of string, date, boolean, object, and variant. Constants:The fixed value known as a constant is one that cannot be changed while a program is running. Syntax:  Const <<constant_name>> As <<constant_type>> = <<constant_value>> Example:  Private Sub CommandButton1_Click() Const MyInteger As Integer = 10 Range(“A1”).Value= MyInteger Const MyDay As String = Sunday Range(“C1”).Value= MyDay End sub If, If-Else, For and While Loop If Statement The ‘If statement’ is a conditional statement. It consists of an if statement followed by another statement. If the condition is true, the codes under the If statement are executed. Syntax for If statement: If(boolean_expression) Then    Statement 1    …..    …..    Statement n End If Example: Program to show the implementation of if statement. Private Sub CommandButton1_Click() Dim score As Integer, result As String Score = Range(“A1”).Value If score >= 10 Then result = “First” Range(“B1”).Value = result End sub If Else Statement The ‘If statement’ is a conditional statement. This statement consists of an “If” expression followed by another “Else” expression. If the condition is true, the lines under the body of the If statement are executed and if the condition is false, it executes the line under the Else Part. Example: Program to show the implementation of if statement. Private Sub CommandButton1_Click() Dim A As Integer Dim B As Integer A = 1500 B = 1000 If A > B Then MsgBox “A is greater” Else MsgBox “B is greater” End If End sub For Loop:  For loop is a control flow statement. In this, the user can write a loop that can be executed repeatedly till it satisfies the condition. Example: Program to show the implementation of for loop. Private Sub CommandButton1_Click() Dim A As Integer A = 1500 For i = 0 To Step 2 MsgBox “The value is: ” & i Next End sub:  While Loop: When statements are true in a while loop, they are carried out until the Wend keyword is reached. The loop is ended and the subsequent statement is executed if the statement is false. Syntax:  While condition(s)    [statements 1]    [statements 2]    …    [statements n] Wend Functions and Sub Procedures Functions: Code that can be reused and called repeatedly throughout a program is called a function. The code can be reused numerous times in your program. Go to Insert and then click on Module in the VBA window to create the function. This function will call the below code. The result will be Sub Procedures: With some minor exceptions, sub-procedures and functions are similar. The call keyword is not required to invoke the sub-procedure because it does not return a value. Example: Program to calculate area using sub procedures. Explore our Business Analytics Programs from World's Top Universities Business Analytics Certification Programme Busines Analytics EPGP - LIBA Professional Certificate Program in Data Science and Business Analytics Master of Science in Business Analytics Global Master Certificate in Business Analytics Busines Analytics Certification - upGrad Conclusion The basic concept of VBA is described here. This simple, but powerful programming language was developed by Microsoft Corp. The use of Excel VBA, and different types of keywords are illustrated here. Various examples are represented to give an idea about the implementation of an if statement, if else statement, while loop, for loop, etc. Try pursuing Business Analytics Certification Program from upGrad which will give you an edge over others in the competitive world. 

Introduction  Dealing with enormous amounts of data is one of the main challenges in data analytics. It would be unnecessary and even impossible to analyze the entire population whenever you undertake research on a specific group. So how can we solve this issue? Is it possible to select a portion of the data to serve as a representative sample of the complete dataset? It appears that there is. Without looking at the complete dataset, you can do research using a variety of sampling strategies used in data analytics. In this article, we’ll learn about what sampling is, how it functions, different types of sampling techniques, and how to decide on the type of sampling to use. Dive deep into the world of sampling and similar concepts by pursuing an Executive PG Program in Business Analytics from LIBA. What is Sampling?  Sampling is a technique for choosing certain individuals or a small portion of the population in order to draw conclusions about the population as a whole and determine its characteristics. Researchers frequently utilize various sampling techniques in market research so they do not have to study the full community in order to gather useful information. Consider the case where we would like to know the proportion of bike users in a particular city. Calling everyone in the city and asking what kind of mode of transport they use is one method to go about this. The alternative would be to ask the same question of a smaller subgroup of people and then use the results to estimate the size of the entire population.   But this procedure is more complicated than it seems. Your sample size ought to be perfect whenever you use this procedure; it shouldn’t be either too big or too tiny. Once the size of your sample has been determined, you must then gather a sample from the population using the appropriate sampling techniques. Every sampling method ultimately falls into one of two basic categories: Probability sampling and Non-probability sampling. Learn business analytics courses online from the World’s top Universities. Earn Masters, Executive PG Programmer Certification, or Global Master Certification to fast-track your career. Types of Sampling: Sampling Methods There are two types of sampling methods used in market action research: probability sampling and non-probability sampling. Let’s examine these two sampling techniques in more detail. Probability sampling: In this sampling strategy, a researcher chooses a few criteria and randomly selects individuals from a population. With the use of this selection option, each member has an equal chance of taking part in the sample. Non-probability sampling: In non-probability sampling, participants are chosen at random for the study. This type of sampling is not a set or predetermined selection procedure. This makes it challenging for every component of the population to have an equal chance of being included in a sample. Check out our free courses related to upskill yourself. Examples Probability Sampling Methods: Selecting a random sample of 50 employees from a company’s employee database. Dividing a population of students into strata based on their grade levels and then randomly selecting a sample from each stratum. Dividing a city into different neighborhoods, randomly selecting a few neighborhoods, and then surveying all households within the selected neighborhoods. Non-probability Sampling Methods: Conducting on-the-spot interviews with people passing by in a shopping mall. Selecting specific individuals who possess the desired characteristics for a study, such as selecting expert witnesses for a legal case. Starting with a few initial participants and asking them to refer other potential participants for a study on a sensitive topic like illegal drug use. Population vs Sample Every researcher needs to be able to understand the difference between the population and the sample. It is simple to figure out the distinction between a population and a sample. One essential rule of statistics that you must always keep in mind is that a sample is always a smaller group (subset) inside the population. Every study in market research and statistics has a central question in mind. The outcome of this investigation is determined by observation and experiment with a population sample size. Insights that explain a phenomenon throughout the population are gained through this process. Population  We are all aware of what the term “population” means. It is often employed to refer to the total number of people residing in a particular region of our nation or state. In research, a population is a complete set of components connected by a common parameter. It’s not necessary for the ‘population’ in the study to be human. Any data parameter that contains a common characteristic qualifies. Sample  A sample is a more limited representation of the population as a whole. It is an accurate representation of the study’s population. The population members who are asked to do the survey constitute the representative sample while surveys are being conducted. As a result, a sample is a subset or subgroup of the population. This sample can be examined to learn more about the traits or actions of the total population. Numerous research techniques, including probability sampling and non-probability sampling, are used to create data samples. Depending on the type of study and the needed level of information, several sampling techniques are used. Sampling frame The objects in your population are listed in a sampling frame. It is an exhaustive list of all the people or things you want to study. A population and a sampling frame differ in that a population is more general and a frame is more particular. However, you can’t just use any list you find. To ensure that your sampling period meets your demands, caution must be used. Because of this, a sampling frame needs to:  Include everyone who belongs to the target population. Include no one who is not a member of the target population. Contains precise data that can be utilized to get in touch with particular people. Sample Size  The phrase “sample size” in market research refers to the total population of participants in the study. Based on factors such as age, gender, and geographic area, researchers select their sample. It may be general or precise.  For instance, you might be interested in learning what consumers between the ages of 30-45 think about your product. Also providing you with a wide population range is the option of merely requiring that your sample reside in India. The sample size is the total number of people included in a sample. Learn more about these methods and terms via Professional Certificate Program in Data Science and Business Analytics.  Probability Sampling Methods One of the important categories of sampling techniques is probability sampling. Every member of the population has a chance to be chosen via probability sampling. , it is typically used when you wish to obtain results that are representative of the entire population Simple Random Sampling  In simple random sampling, every observation in the population has an equal likelihood of being chosen, and any potential sample of a given size also has an equal chance of being chosen. One way to choose a simple random sample is to sequentially number each unit on the sampling frame and make the selections using random numbers generated by a random number generator. Simple random sampling allows for the selection of the units with or without replacement. In contrast to sampling without replacement, which only allows for a single selection of a unit, replacement sampling permits numerous selections of the units. The most popular technique, absent replacement, is sampling. Example: Depending on the size of your firm, the researcher gives each member of a database of companies a number between 1 and 1000 before using a random number generator to choose 100 individuals. Systematic Random Sampling The first object from the population is randomly chosen by the researcher as part of systematic random sampling. The researcher will then pick the nth object from the list for each choice. Systematic random sampling is a fairly simple process that can be carried out manually. Unless specific demographic traits are reproduced for every nth object, the results are representative of the population. Example: Every individual in the company database is given a number by the researcher. Instead of creating numbers at random, a random beginning point (let’s say 10), is chosen. The researcher then chooses, say, every tenth individual on the list (20, 30, 40, and so on) until the sample is collected. Stratified Random Sampling In stratified random sampling, the total population is separated into several distinct, homogenous groups (strata), and final participants are randomly selected from the strata for study. To ensure that every group member has an equal chance of being chosen using basic probability, the members of each group should be different.  Example: The researcher wants to make sure that the sample accurately reflects gender in a company that has 200 female employees and 600 male employees. So, based on gender, the population is split into two sections.  Cluster Sampling  Cluster sampling divides the population into smaller groups, yet each group shares traits with the entire sample. You choose an entire subgroup at random as opposed to choosing a sample from every subgroup. When working with sizable and diverse populations, this approach is useful. Example: A fast-food chain has more than a hundred locations in 10 cities throughout the globe, with nearly the same number of staff members working in comparable positions. Then, two or three offices are chosen at random by the researcher and used as the sample. Uses of Probability Sampling Probability sampling has several applications, including: Reduce Sample Bias: When using the probability sampling approach, the sample that is drawn from a population has little to no research bias. The sample choice primarily reflects the researcher’s comprehension and conclusions. Data gathering through probability sampling results in higher-quality data since the sample accurately represents the population. Population Diversity: It’s crucial to have enough representation in large, diverse populations to prevent statistics from being biased towards one demographic. Create an Accurate Sample: Probability sampling assists in the planning and production of an accurate sample by the researchers. This makes it easier to get precise data. Non-probability Sampling Methods Non-probability sampling limits the possibility that each person will be selected for the sample. Although easier and less expensive, this sampling technique carries a significant risk of bias. It is frequently employed in qualitative and exploratory research with the goal of gaining a basic understanding of the community. Convenience Sampling  The simplest sampling technique is convenience sampling, where participants are chosen based on their availability and desire to take part in the survey. The sample could not be representative of the population as a whole, hence the results are subject to severe bias. Example: The surveys that are done on YouTube or Facebook. People who are interested in participating in the survey or poll will show up, but the outcomes may not be reliable because they are highly biased. Voluntary Response Sampling Similar to convenience sampling, voluntary response sampling depends only on participants’ willingness to participate. However, people volunteer themselves rather than being selected by the researcher.  Example: The researcher offers the option for participation in a survey that is sent to every employee of a company. Purposive Sampling Technique In the Purposive sampling technique, a researcher uses discretion in selecting individuals from the population to take part in the study. Researchers frequently think they can use good judgment to gather a representative sample while also saving time and money There is a likelihood that the results will be extremely accurate with a small margin of error because the researcher’s knowledge is required to generate a sample in this sampling technique. Ex: A television network wishes to investigate one of its programmes. The target audience is known to the researcher, who can then select participants from the target audience for the study. Snowball Sampling Technique  This sampling strategy involves primary data sources suggesting other potential primary data sources that could be used in the investigation. The snowball sampling strategy depends on recommendations from the initial participants to generate more subjects. As a result, sample group members are selected using this sampling technique via chain referral.  In the social sciences, this sampling technique is widely used for studying hard-to-reach groups. The sample expands like a snowball when more candidates who are known to the existing candidates are nominated. Example: Finding people with uncommon disorders who are willing to participate in research could be challenging for a pharmaceutical business. By asking them to refer participants from their contacts, the pharma manufacturer can recruit a small number of people to take part in the clinical study. Explore our Business Analytics Programs from World's Top Universities Business Analytics Certification Programme Busines Analytics EPGP - LIBA Professional Certificate Program in Data Science and Business Analytics Master of Science in Business Analytics Global Master Certificate in Business Analytics Busines Analytics Certification - upGrad Uses of Non-probability Sampling Non-probability sampling has several applications, including: Creating hypothesis: When there is little to no prior knowledge available, researchers employ the non-probability sampling method to make an assumption. This technique aids in the quick return of data and creates a foundation for additional study. Exploratory research: When performing exploratory research, pilot studies, or qualitative research, researchers frequently employ this sample strategy. Budget and time restrictions: The non-probability technique is used when these factors are present and preliminary data must be gathered. It is simpler to choose respondents at random and have them complete the survey or questionnaire because the survey design is flexible. Acquire the deeper understanding of sampling analysis with the Business Analytics Certification Program from upGrad.  How do you Decide on the Type of Sampling to Use? To achieve your research objectives, it is crucial to select a sampling technique carefully. Your sampling’s effectiveness will depend on a number of variables. Here are several procedures used by professionals to select the most appropriate sampling strategy. Note the objectives of the study. Typically, it has to be a combination of cost, accuracy, and precision. Determine the efficient sampling strategies that could possibly meet the research objectives. Test each of these strategies to see if they assist you in achieving your objective. Pick the approach that suits the research the best. Difference Between Probability Sampling and Non-probability Sampling Methods Basis Probability Sampling Technique  Non-Probability Sampling Technique Definition  In this technique, samples from a larger population are selected using a process based on the theory of probability.  In this technique, samples are chosen by the researcher based on their own judgment rather than by random selection. Nature  The research conducted is definitive. The research conducted is exploratory. Sample  The sample is selected using a procedure, so the demographics of the population are clearly represented. The depiction of the population’s demographics tends to be biased because the sampling methodology is random. Time Takes longer to complete since the selection criteria are defined by the research design before the market research study starts. Since neither the sample nor its selection criteria are ambiguous, this kind of sampling technique is quick. Hypothesis  Prior to the study’s start, there is a guiding hypothesis in probability sampling, and this approach seeks to substantiate it. In non-probability sampling, the hypothesis is created after the research study has been completed. Result  The results of this kind of sampling are conclusive since it is completely unbiased. Because of the complete bias of this form of sampling, the findings are also biased, making the research questionable.   Conclusion  The entire subject of probability and non-probability sampling procedures is covered in this article. Prior to beginning any form of research, it is crucial to select the appropriate sample methods. The sample you select will have a significant impact on the success of your study. There are many more sampling procedures from which to choose in order to hone your study; these are simply the top ones. It’s very important to be certain of the appropriate sampling technique to utilize and at what times you want to succeed as a business analyst. If you want to learn more about business analytics, you may check out upGrad’s Global Business Analytics Programme, which is offered in collaboration with Michigan State University. It offers a variety of learning resources, including live faculty engagement, interactive discussion boards, quizzes, and assignments, career counseling, interview preparation, and much more. Get started with this course right away to launch a successful business analytics career.

Excel is a powerful spreadsheet software widely used in businesses, organizations, and personal finance management. Whether you’re a beginner or an experienced user, improving your Excel skills can significantly enhance your productivity and efficiency. In this guide, we’ll explore the top 15 actionable tips to help you level up your Excel proficiency. From mastering basic knowledge of excel to utilizing advanced features, these tips will empower you to work more effectively with data, automate tasks, and create sophisticated spreadsheets. So let’s dive in and discover how you can improve your Excel skills and become a true Excel wizard. Master of Science in Business Analytics from GGU is one way to become an excel wizard and a Business Analyst. What are considered advanced-level Excel skills? Advanced-level Excel skills encompass a range of techniques and functionalities that go beyond the basic knowledge of excel. These skills involve the ability to work with complex formulas, manipulate data using advanced functions, analyze data with pivot tables and charts, automate tasks using macros, and create interactive dashboards. Mastering these advanced Excel skills allows users to handle large datasets efficiently, perform complex data analysis, and create dynamic reports and visualizations. In the following sections, we will delve into these skills and provide actionable tips to help you enhance your proficiency in Excel. Basic Excel skills These include tasks like data entry, basic formulas (e.g., SUM, AVERAGE), cell formatting, sorting and filtering data, and creating simple charts. Users should be comfortable with navigating worksheets, managing basic functions like copy and paste and performing basic calculations using arithmetic operators. Intermediate Excel skills These involve working with more complex formulas (e.g., IF, VLOOKUP), conditional formatting, data validation, pivot tables, and functions like COUNTIF and SUMIF. Users should also know advanced formatting options, creating and modifying charts, and utilizing features like filtering, subtotaling, and named ranges. Advanced Excel skills These encompass proficiency in advanced formulas (e.g., INDEX-MATCH, array formulas), pivot tables and slicers, macros and automation, data analysis tools (e.g., Goal Seek, Solver), advanced charting techniques, data modeling, Power Query, and Power Pivot. Users can perform complex data manipulations, create interactive dashboards, and conduct in-depth data analysis. Learn business analytics courses online from the World’s top Universities. Earn Masters, Executive PG Programmer Certification, or Global Master Certification to fast-track your career. What jobs can you do with advanced Excel skills? Having advanced MS Excel skills opens up a wide range of job opportunities across various industries. Additionally, advanced Excel important topics are valuable in fields like accounting, marketing, human resources, and consulting, where the ability to handle complex data and generate insights is crucial for decision-making and problem-solving. Become a professional in Analytics with the help of Executive PG Program in Business Analytics from LIBA. Data Analyst Advanced Excel skills are crucial for a data analyst, as they involve working with large datasets, performing data cleansing and manipulation, creating complex formulas and functions, and generating insightful reports. Excel’s features like pivot tables, Power Query, and data analysis tools aid in data exploration, visualization, and extracting valuable insights. Accountant Excel knowledge is fundamental for accountants. Advanced Excel skills are essential for tasks such as financial modeling, budgeting, forecasting, and financial analysis. Accountants use advanced functions, formulas, and features like conditional formatting, data validation, and pivot tables to manage and analyze financial data accurately and efficiently. Information Clerk Advanced Excel skills allow information clerks to organize and analyze data efficiently. They can utilize Excel’s features to sort and filter data, perform calculations, create charts and graphs, and generate reports. Skills in advanced formulas, functions, and data manipulation techniques help information clerks handle and present data effectively. Check out our free courses related to upskill yourself. Business Analyst Advanced Excel skills are vital for business analysts as they involve data analysis, trend identification, and report generation. Excel’s capabilities in data manipulation, advanced formulas, pivot tables, and data modeling help business analysts analyze and interpret complex business data, perform forecasting, identify patterns, and make informed decisions. Market Analyst Excel is a powerful tool for market analysts. Advanced MS Excel skills enable them to process and analyze market data, conduct statistical analysis, perform regression analysis, and build forecasting models. They can use Excel’s advanced functions, data analysis tools, and charting features to extract insights, monitor market trends, and make strategic recommendations. Financial Analyst Advanced Excel skills are a must for financial analysts. They use Excel to perform financial modeling, analyze financial statements, conduct ratio analysis, create dynamic financial reports, and build valuation models. Proficiency in functions like NPV, IRR, and financial functions allows financial analysts to perform complex calculations and support investment decisions. Auditor Excel plays a critical role in the work of auditors. They use it to import and analyze financial data, perform audit tests, validate formulas, and identify anomalies or errors. Excel important topics, including data validation, conditional formatting, advanced filtering, and auditing tools, help auditors efficiently review financial information and maintain data integrity. Cost Estimator Advanced MS Excel skills are valuable for cost estimators. They can use Excel to create detailed cost models, perform cost analysis, estimate project budgets, and track expenses. Advanced functions like lookup functions, statistical functions, and financial functions enable cost estimators to calculate costs accurately and efficiently, improving cost estimation and project planning. Top 20 advanced Excel skills Masters these skills and apply them practically with the help of a Professional Certificate Program in Data Science and Business Analytics.  Data consolidation: Excel allows you to consolidate data from multiple sources or worksheets into a single location, making it easier to analyze and summarize information. Data selection: Mastering advanced techniques for selecting and highlighting specific data ranges enables efficient analysis and manipulation of large datasets in Excel. Quality control: Advanced Excel skills include using functions and tools to ensure data accuracy, detecting errors, and conducting quality control checks. Visual representations: Excel offers various tools for visually representing data, such as charts, graphs, and conditional formatting, making it easier to interpret and communicate information effectively. Power Query: This powerful tool enables users to import, transform, and clean data from multiple sources, providing a streamlined process for data manipulation and analysis. Conditional formatting: Advanced Excel users leverage conditional formatting to automatically format cells based on specific conditions, enhancing data visualization and highlighting important information. Advanced charting: Excel’s advanced charting capabilities allow users to create dynamic and interactive charts, including pivot charts, trendlines, and customized chart templates. PivotTables: With PivotTables, users can summarize and analyze large datasets, quickly generating meaningful insights and facilitating data exploration and decision-making. Flash Fill: This feature automatically fills in values based on patterns recognized in the data, saving time and effort in data cleaning and transformation tasks. Filters: Advanced filtering techniques in Excel help users efficiently sort, filter, and extract specific data based on various criteria, enabling focused analysis and data extraction. COUNTIF: The COUNTIF function counts cells that meet specified criteria, allowing users to quickly calculate frequencies or track occurrences of specific values in a dataset. Sparklines: Excel’s sparklines provide compact, data-rich visualizations within cells, enabling users to quickly assess trends and patterns within datasets. Data validation: Advanced Excel users utilize data validation techniques to set rules and restrictions on data entry, ensuring data integrity and minimizing errors. Data manipulation: Advanced Excel skills involve utilizing formulas, functions, and tools to manipulate and transform data efficiently, such as merging datasets, splitting columns, and cleaning data. Macros: Macros allow users to automate repetitive tasks in Excel by recording and running a series of commands, significantly increasing productivity and efficiency. VLOOKUP: The VLOOKUP function searches for a value in a specified range and returns a corresponding value from a different column, making it a powerful tool for data retrieval and analysis. INDEX: The INDEX function allows users to retrieve values from a specific row and column in a range, providing flexibility and control in data extraction and analysis. MATCH: The MATCH function identifies the position of a value within a range, enabling users to locate and work with data based on specific conditions or criteria. Data simulations: Excel’s data simulation capabilities, using tools like Monte Carlo simulations, enable users to model and analyze possible outcomes based on probabilistic scenarios. IFERROR: The IFERROR function helps handle errors in formulas by providing alternative values or actions when an error occurs, improving the robustness and accuracy of calculations and data analysis. Explore our Business Analytics Programs from World's Top Universities Business Analytics Certification Programme Busines Analytics EPGP - LIBA Professional Certificate Program in Data Science and Business Analytics Master of Science in Business Analytics Global Master Certificate in Business Analytics Busines Analytics Certification - upGrad How can I improve my advanced Excel skills? Online Tutorials and Courses: Explore online platforms that offer comprehensive Excel tutorials and courses, including video lessons and practice exercises. Websites like Microsoft Learn, LinkedIn Learning, and Udemy provide a wide range of Excel courses suited for various skill levels. Practice with Real-World Data: Find datasets related to your field of interest and practice analyzing and manipulating them in Excel. This hands-on experience will enhance your skills and help you understand how Excel can be applied in practical scenarios. Excel Forums and Communities: Engage with Excel forums and communities to seek advice, ask questions, and learn from experienced users. Platforms like Excel Reddit and Excel Forum offer a wealth of knowledge shared by Excel enthusiasts and experts. Experiment with Advanced Features: Challenge yourself to explore advanced Excel features like macros, Power Query, Power Pivot, and data analysis tools. Experimenting with these features will expand your knowledge and allow you to tackle complex tasks efficiently. Stay Updated: Excel is continually evolving, with new features and enhancements being introduced. Stay up to date with Excel news, blogs, and tutorials to keep your skills current and take advantage of the latest functionalities. What Can You Do With Excel Skills? Proficiency in Excel opens doors to various career opportunities across industries. You can pursue roles such as data analyst, financial analyst, business analyst, project manager, accountant, market researcher, and administrative professional. Excel skills are valuable in tasks such as data analysis, financial modeling, reporting, budgeting, forecasting, project management, and process automation. Regardless of the industry, Excel expertise equips you with the ability to manipulate data, derive insights, and make informed decisions, making you a valuable asset to any organization. Read our Other Articles Related to Business Analytics What is Business Analytics? Career, Salary & Job Roles Top 7 Career Options in Business Analytics Business Analytics Free Online Course with Certification Business Analytics Vs Data Analytics: Difference Between Business Analytics and Data Analytics Top 7 Best Business Analytics Tools Recommended for every Business Analyst Top 11 Industry Applications of Business Analytics Future Scope of Business Analytics Business Analytics Eligibility or Requirement 8 Business Analytics Tips: Which Helps to Run Business Successfully Conclusion In conclusion, honing your advanced Excel skills can greatly enhance your professional prospects and versatility. By leveraging online resources, practicing with real-world data, engaging with Excel communities, exploring advanced features, and staying updated, you can continue to refine your Excel proficiency. With Excel skills, you can pursue a diverse range of career paths and contribute significantly to data analysis, financial management, project planning, and decision-making in various industries. Embrace the power of Excel and unlock your potential for success. Another way to achieve success in this industry is pursuing Business Analytics Certification Program from upGrad.

Requirement elicitation is a crucial phase in any software development project, as the success of a project largely depends on how well the requirements are understood, communicated, and managed. This article delves into What is requirement elicitation, different requirement elicitation techniques and more. Requirements elicitation Activities Requirements elicitation in software engineering is the process of gathering information from stakeholders and subject matter experts to understand their needs, expectations and requirements for a project. It implicates effective communication, active listening and careful analysis of the information gathered from various sources, including interviews, surveys and stakeholder workflow observation. The requirement elicitation techniques process involves: Identifying stakeholders: Determining who will be involved in the project and who will be affected by its outcome. Needs and expectations: Understanding the needs and expectations of different stakeholders and prioritizing them. Documenting requirements: Creating a comprehensive and organized set of requirements used as a reference throughout the project. Golden Gate University (GGU) in San Francisco offers a Master of Science in Business Analytics program for working professionals and graduates who want to advance their careers in the Business Analytics field. The program is taught by experienced GGU professors. The curriculum covers data analysis for managers, business intelligence, advanced statistical analysis, natural language processing and machine learning topics. Students also have the opportunity to specialize in concentrations such as marketing analytics, financial analytics, supply chain analytics, and healthcare analytics.  Learn business analytics courses online from the World’s top Universities. Earn Masters, Executive PG Programmer Certification, or Global Master Certification to fast-track your career. Requirements Elicitation Methods and Techniques Interviews Interviews are one-on-one or group discussions with stakeholders to gather information about their needs, expectations, and concerns. This requirement elicitation in software engineering technique is highly effective as it allows for direct communication between the analyst and stakeholders. Critical Aspects of Interviews: Conducted in person, over the phone, or video conferencing Allows for clarification and follow-up questions Provides an opportunity to establish rapport with stakeholders Require multiple sessions to cover all topics Brainstorming Sessions Brainstorming sessions involve a group of stakeholders coming together to generate ideas and potential solutions for the project. These sessions can be highly productive and lead to innovative solutions.  Critical Aspects of brainstorming sessions: Encourages creative thinking and idea generation Involves multiple stakeholders, ensuring diverse perspectives Requires a skilled facilitator to keep the discussion focused and productive Ideas generated need further refinement and analysis Facilitated Application Specifications Facilitated application specifications have a structured meeting of stakeholders to develop a model or prototype of the project. This technique is more outcome-oriented and can result in a tangible deliverable.  Critical Aspects of facilitated application specifications: Typically facilitated by a business analyst or professional facilitator Have stakeholders working together to build a model or prototype More structured and outcome-oriented than other techniques Require multiple sessions to develop a comprehensive model or prototype Check out our free courses related to upskill yourself. Quality Function Deployment Quality function deployment (QFD) is a technique to translate customer needs and expectations into specific product features or requirements. It involves the use of matrices and charts to prioritize and manage requirements.  Critical Aspects of QFD: Focuses on customer needs and expectations Uses quantitative methods to prioritize requirements Provides a visual representation of the relationship between customer needs and product features Can be time-consuming and complex to implement  In today’s rapidly evolving world, data science and artificial intelligence are prospering career fields offering many growth opportunities in research, engineering, cybersecurity, analytics, and marketing. Loyola Institute of Business Administration recognizes the immense potential of these fields and has designed an Executive PG Program in Business Analytics from LIBA to cater to the growing demand for specialized skills in this area. LIBA has earned several accreditations and covers data visualization, data analytics, and statistical analysis. Use Case Approach The use case approach implicates developing scenarios to describe how the end-users will interact with the system. These scenarios identify the necessary functionalities and requirements for the project.  Critical Aspects of the use case approach: Focuses on end-user interactions with the system Helps to identify necessary functionalities and requirements Provides a clear and concise representation of user interactions Require multiple iterations to develop comprehensive use cases Stakeholder Analysis Stakeholder analysis is the process of identifying all relevant stakeholders and their needs, expectations, and level of influence on the project. This requirement elicitation in software engineering technique helps to ensure that all stakeholder perspectives are considered during the requirement elicitation process. Critical aspects of stakeholder analysis: Identifies all relevant stakeholders and their roles Provides a clear understanding of stakeholder needs and expectations Helps to prioritize stakeholder requirements based on their level of influence Requires a thorough understanding of the project and its stakeholders Focus Group A focus group is a moderated discussion involving a small group of stakeholders. The purpose is to gather diverse perspectives on the project requirements and explore potential issues or opportunities.  Critical Aspects of focus groups: Involves a small group of stakeholders representing diverse perspectives Requires a skilled moderator to facilitate the discussion Give opportunity to explore potential issues or opportunities Require multiple sessions to gather comprehensive feedback Interface Analysis Interface analysis involves examining the interactions between the proposed system and its external components, such as other systems, users, or devices. This requirement elicitation technique identifies prerequisites related to these interactions. Critical Aspects of interface analysis: Focuses on the interactions between the system and its external components Helps to identify requirements related to these interactions Requires a thorough understanding of the system and its external components Involve the use of diagrams or models to represent the interactions  Observation Observation involves monitoring and recording how users perform tasks, use tools, and interact with the system. This elicitation in software engineering technique help to gain practical insights into the system’s usage and identify areas for improvement. Critical Aspects of Observation: Provides an understanding of stakeholder needs and expectations Can be conducted in person or remotely using video recordings or screen-sharing tools Active observation involves asking questions and attempting the work of others Passive observation involves silently observing others’ work without interrupting Requires careful planning and documentation to ensure accurate results Time-consuming and resource-intensive technique Prototyping Prototyping involves creating a preliminary model or version of the system to gather feedback from stakeholders. This technique allows stakeholders to interact with the proposed system and identify potential issues or improvements.  Critical Aspects of Prototyping: Provides a tangible representation of the proposed system, involves creating mock-ups, diagrams, or site layouts Allows stakeholders to provide feedback based on actual interactions Used to test and refine requirements throughout the development process Require significant time and resources to develop and update prototypes Survey Surveys involve collecting information from stakeholders through questionnaires or other structured forms. This elicitation in software engineering technique is used to gather feedback from a large number of stakeholders quickly and efficiently. The responses are then analyzed to identify areas of interest and prioritize requirements. Critical Aspects of Surveys: Can be conducted online or using paper forms Allows for the collection of feedback from a large number of stakeholders Provides a structured format for gathering information Provides accurate information compared to interviews May require follow-up surveys based on participant responses In today’s data-driven world, professionals need to have a deep understanding of data science and business analytics to make informed decisions. UpGrad Professional Certificate Program in Data Science and Business Analytics program helps learners identify insights, improve their ability to make predictions and make better decisions. The program is curated for technical and non-technical professionals with the growing importance of data-driven decision-making across all industries. Explore our Business Analytics Programs from World's Top Universities Business Analytics Certification Programme Busines Analytics EPGP - LIBA Professional Certificate Program in Data Science and Business Analytics Master of Science in Business Analytics Global Master Certificate in Business Analytics Busines Analytics Certification - upGrad Advantages of Requirement Elicitation Ensures a thorough understanding of stakeholder needs and expectations Supports effective communication among stakeholders Helps prioritize requirements based on stakeholder input Identifies potential risks and issues early in the project Enhances collaboration and teamwork among stakeholders Increases the likelihood of project success Provides a foundation for project planning and execution Reduces the risk of project scope creep and rework Disadvantages of Requirement Elicitation Requirement Elicitation techniques can be time-consuming and resource-intensive Requires commitment from all participants Involve complex and challenging communication among stakeholders Can be difficult to reach a consensus on requirements Some elicitation techniques may not be suitable for all projects or situations Read our Other Articles Related to Business Analytics What is Business Analytics? Career, Salary & Job Roles Top 7 Career Options in Business Analytics Business Analytics Free Online Course with Certification Business Analytics Vs Data Analytics: Difference Between Business Analytics and Data Analytics Top 7 Best Business Analytics Tools Recommended for every Business Analyst Top 11 Industry Applications of Business Analytics Future Scope of Business Analytics Business Analytics Eligibility or Requirement 8 Business Analytics Tips: Which Helps to Run Business Successfully Conclusion Requirement elicitation techniques play a vital role in the software development process by ensuring the development team has a clear and comprehensive understanding of the customer’s needs and requirements. These techniques facilitate effective communication and collaboration to identify potential risks and problems early in the development cycle. By selecting and employing appropriate requirements elicitation techniques, software development teams can increase the chances of developing a software system that meets customer needs and expectations. Kickstart your career in business analytics with UpGrad’s Business Analytics Certification Program. The course covers statistical modeling, optimization, predictive analysis, and managerial roles, among other topics. Students can also benefit from networking opportunities and personalized industry guidance.

The world of data analytics is fascinating. After all, isn’t it amazing to deconstruct data, delve into it, and gather meaningful patterns from within? Given how data has shaped our world, it only makes sense to localize data analytics into every data-rich domain. So when it comes to finance, analytics plays essentially the same roles as it does in other areas – it provides a window to derive insight based on which organizations can make sound financial decisions.  How does financial analytics work in an organization? Financial analytics can be thought of as the backbone of any organization, which powers other functions with the fuel to run smoothly. To extend this analogy, if financial data analytics holds up the company at a financial level, the HR function will ensure enough employee engagement at the company level. Thus, these wings come together to create the organization’s nervous system. The basic idea behind this analogy is to convey that organizational functions are interrelated – one cannot exist without the other. Beginning on this note of interconnectedness, we can say that financial data analytics helps identify which decisions are financially sound and which aren’t. A good example of this is – continuing the analogy mentioned earlier – how much money to spend on attracting good candidates versus retaining candidates. Taking this decision becomes easier with financial analytics because it provides deep insights into the data collected.  Explore our Business Analytics Programs from World's Top Universities Business Analytics Certification Programme Busines Analytics EPGP - LIBA Professional Certificate Program in Data Science and Business Analytics Master of Science in Business Analytics Global Master Certificate in Business Analytics Busines Analytics Certification - upGrad In fact, this interdependence is not just limited to HR but also extends into other areas. For instance, financial analytics determines the budget of a marketing campaign, the funding of different teams in the organization, and much more. Learn Business Analytics Courses online from the World’s top Universities. Earn Masters, Executive PGP, or Advanced Certificate Programs to fast-track your career. The Evolving Landscape of Financial Analytics The Impact of Artificial Intelligence and Machine Learning: Financial data analytics has been transformed by artificial intelligence (AI) and machine learning (ML). These technologies allow organizations to process massive volumes of data in a timely and reliable manner. Algorithms driven by AI can discover patterns, detect anomalies, and estimate future trends, improving the accuracy of financial projections. Furthermore, ML algorithms automate monotonous processes, allowing analysts to focus on strategic decision-making. Real-time Data Analytics: In the financial business, real-time data analytics is becoming increasingly important. With the advancement of technology, businesses can now analyze data as it is created, allowing for speedy decision-making. Real-time analytics may help you understand market trends, consumer behavior, and risk management. It enables organizations to adapt quickly to changing market circumstances, optimize trading tactics, and efficiently minimize risks. The Role of Blockchain in Financial Analytics: Because of its capacity to improve security and transparency, blockchain technology has gained traction in financial data analytics. Blockchain provides data integrity and reduces the danger of fraud or manipulation by utilizing decentralized ledgers. Financial organizations may use blockchain to increase transaction security and efficiency, as well as to improve audit trails and expedite compliance processes. However, blockchain application in financial data analytics necessitates careful consideration of scalability, legal frameworks, and interoperability issues. Advanced Visualization Techniques: Effective data visualization is paramount in financial analytics to comprehend complex data sets and communicate insights. Advanced visualization techniques, such as interactive dashboards and visual analytics tools, enable users to explore financial data intuitively. By presenting data visually, organizations can identify trends, outliers, and patterns more easily. Visualizations also facilitate effective communication of insights across departments, aiding in decision-making processes. The Importance of Data Visualization in Financial Analytics Data visualization plays a pivotal role in financial analytic tools, enabling organizations to make sense of vast amounts of complex data. It goes beyond presenting numbers and charts; it transforms raw data into meaningful insights that drive informed decision-making. Here are some key reasons why data visualization is crucial in financial analytics: Enhanced Data Exploration: Interactive visualizations empower users to explore financial data analytics more dynamically and intuitively. With interactive features like filtering, zooming, and drill-down capabilities, analysts can dive deeper into the data, uncovering hidden insights and discovering valuable correlations. This fosters a deeper understanding of financial trends and helps identify potential risks and opportunities. Effective Communication of Insights: Data visualization facilitates effective communication of insights across departments and stakeholders. Visual representations make it easier to convey complex financial information in a digestible format. Whether it’s presenting financial reports to executives, collaborating with team members, or explaining data-driven recommendations, visualizations enhance communication and promote a shared understanding of the data. Rapid Decision-Making: In today’s fast-paced business environment, quick decision-making is essential. Data visualizations enable stakeholders to absorb information rapidly and make informed decisions promptly. Visual representations provide a holistic view of financial data, enabling users to identify trends, outliers, and potential risks promptly. This agility is crucial in seizing market opportunities and addressing emerging challenges effectively. Identifying Key Performance Indicators (KPIs): Data visualizations assist organizations in identifying and tracking key performance indicators (KPIs). Businesses may monitor their financial health, gauge progress, and take proactive changes if performance deviates from planned objectives by visualizing KPIs in real-time. This enables organizations to stay on track with their strategic objectives and make data-driven changes as needed. Types of Financial Analytics 1. Sales analytics A fairly obvious area where financial analytics can genuinely add value is sales analytics which can predict how fast a company will grow and by how much. This is almost the foundational level of financial analytics data basis on which other decisions are made. For example, sales analytics can point out which products garner maximum sales. So, if there aren’t enough people on the team to support creating new products in that department or for customer service, the company will know it needs to hire more people.  2. Profitability analytics (across functions) This is one branch of analytics that concerns itself with making sure that the company never loses track of where it’s headed, regardless of how many clients it or products it has on paper. Fundamentally, business engagements can either make money for an organization or add to its cost. Each organization must balance these metrics, with an obvious priority placed on profitability. Companies can gain deeper insights into their profit and loss metrics with financial analytics, thereby understanding which direction to take.  3. Cash flow analytics This may not be very apparent when it comes to huge organizations – who have either raised funding or are already in a position where they have steady cash flows – but there is a lot of behind-the-scenes work that goes into it. Some of the metrics used to make this happen include cash conversion and a working capital ratio, and logistic regression becomes the go-to financial analytics tool here. 4. Shareholder value analytics This type of financial analytics provides shareholders more insight into how a company’s stock price behaves. Of course, if the recent massive peaks and troughs in the stock market are any indication, there are a multitude of forces that determine these things. And financial analysis seeks to bring clarity to this confusing situation. This can end up making a huge impact in every imaginable real-world context. Hence, shareholder value analytics is used in conjunction with profitability analytics and cash flow analytics. Depending on the type of value being forecasted, sales analytics may also be used. 5. Value-driven analytics This is perhaps the most visionary of all the types of financial analytics listed here. However,  it is not just a qualitative evaluation of terms. Value-driven analytics typically refer to the actualization of the values set by an organization and how well it’s doing. This analytics ensures that the larger strategic metrics do not fall off the radar – it tries to pin accountability to these strategic metrics by assigning them quantitative data points. Read our Other Articles Related to Business Analytics What is Business Analytics? Career, Salary & Job Roles Top 7 Career Options in Business Analytics Business Analytics Free Online Course with Certification Business Analytics Vs Data Analytics: Difference Between Business Analytics and Data Analytics Top 7 Best Business Analytics Tools Recommended for every Business Analyst Top 11 Industry Applications of Business Analytics Future Scope of Business Analytics Business Analytics Eligibility or Requirement 8 Business Analytics Tips: Which Helps to Run Business Successfully Is Financial Analytics the right choice for you? If you’ve felt confused about whether you should pursue a career in financial analytics, or are struggling to make the decision right now, don’t worry – we have a list that should help you decide! Financial analytics is a field for you if: You feel excited about the prospect of completely getting into the nitty-gritty of an organization’s finances. You can think about the big picture while focusing on the most granular details. You’re fascinated by how data works and want to use it to extract valuable insights. You want to work with numbers, graphs, visualizations and present your work to relevant stakeholders. You believe you have the right mix of curiosity, passion, and dedication for this area of expertise. Most importantly, if you aspire to build a career in finance, this is the most trending option for you! Take your career to the Next Level with upGrad Business Analytics Courses! upGrad offers various courses for finance aspirants who want to capitalize on the available opportunities. For example, with upGrad’s Business Analytics Online Certification course that lasts only three months, you can do actual industry projects to bolster your portfolio. You even get 100+ hours of lessons and placement assistance after course completion! upGrad offers placement assistance for you so that you can apply to various companies even before they open the job posts on multiple portals. Moreover, you also get career assistance and networking opportunities to better prepare for real-world situations.  Depending upon your career requirements, you may consider doing another course from upGrad, such as a Global Master Certificate in Business Analytics .Ultimately, no matter which course of action you choose for yourself, you will learn and grow as a professional!

In today’s rapidly changing business landscape, understanding the needs and expectations of stakeholders has become increasingly important for organisations of all sizes and sectors. Stakeholders can significantly impact an organisation’s operations and success, and failing to consider their needs and interests can lead to negative consequences, such as loss of reputation or decreased customer loyalty. If you’re new in the world of stakeholder matrix and want to learn more, read this article. We will delve deeper into what stakeholder analysis is, its advantages, and examples.  What is Stakeholder Analysis? Stakeholder analysis involves identifying and analysing the interests, needs, expectations, and concerns of all individuals regarding a project, decision, or initiative of an organisation. The goal is to gain a comprehensive understanding of the stakeholders’ perspectives and to use this information for  Informed decision-making Develop effective communication strategies Manage relationships with stakeholders. Stakeholders can include various individuals and groups, such as customers, employees, suppliers, shareholders, regulatory bodies, community groups, and other organisations interested in the organisational activities. The analysis typically involves –  Identifying and categorising stakeholders based on their level of interest in the organisation’s activities Their influence on the organisation Their potential impact on the organisation’s success. What is stakeholder management? Stakeholder management is the process of identifying, assessing and managing the relationships with stakeholders to ensure that their needs and expectations are met. Stakeholder management aims to establish a positive relationship with stakeholders and ensure that they are satisfied with the organisation’s actions and decisions. Ultimately, their say can influence your company’s future. The process includes –  Locating stakeholders Evaluating their requirements and expectations Organising and carrying out various actions to interact with them. Stakeholder Management Strategy Here is what a stakeholder management strategy should look like –  How complicated your project is: You may evaluate this by comparing it to previous projects, looking at the project’s milestones, or looking at the resources needed or the time allotted.  The level of help required to get the desired results: This might involve financial support, professional counsel, tangible assets, content quality checks, and other things. The amount of time you have to communicate: If your project involves a lot of stakeholder input, you should think about how to manage the time you are going to be spending on communication. Types of Stakeholders There are mainly two types of stakeholders –  Internal/direct/primary stakeholders External/indirect/secondary stakeholders Internal  Internal stakeholders include individuals or organisations interested in or concerned about an organisation’s choices or actions. They are also referred to as Direct or Primary stakeholders.  Examples of internal stakeholders –  Employees Managers Board of directors Shareholders Contractors External Stakeholders Those having an interest in a company’s success but are not directly connected to its projects are external stakeholders. They are also referred to as Indirect or Secondary stakeholders.  Examples of external stakeholders –  Customers Suppliers Community groups Government Competitors Media Learn business analytics courses online from the World’s top Universities. Earn Masters, Executive PG Programmer Certification, or Global Master Certification to fast-track your career. Advantages of Stakeholder Analysis Stakeholder analysis offers several advantages to organisations, including – Understanding stakeholder perspectives Companies can better understand their needs and expectations by analysing stakeholders’ perspectives and concerns. This allows them to tailor activities and decisions to meet stakeholders’ needs and build stronger relationships. Mitigating Risks Stakeholder analysis can help organisations identify potential risks and negative impacts of their activities on stakeholders. By understanding the concerns of stakeholders, organisations can take steps to mitigate these risks and minimise negative impacts. Since stakeholders often bring along a significant length of experience, it is wise to obtain their valuable insight and implement it into your project.  Check out our free courses related to upskill yourself. Enhancing decision-making Stakeholder analysis provides organisations with valuable information that can be used to make more informed and effective decisions. By considering the perspectives of all stakeholders, organisations can make decisions that are more aligned with their goals and values. Improving communication Stakeholder analysis can enable organisations to identify the most effective ways to communicate with stakeholders. Businesses can tailor their communication strategies to build stronger relationships and promote transparency by understanding stakeholders’ communication preferences and needs. Becoming Successful Project success and its related effects are significantly influenced by stakeholders’ attitudes. You may also land new jobs by anticipating stakeholder expectations and delivering results. This is key in helping organisations stay ahead of the competition.  Explore our Business Analytics Programs from World's Top Universities Business Analytics Certification Programme Busines Analytics EPGP - LIBA Professional Certificate Program in Data Science and Business Analytics Master of Science in Business Analytics Global Master Certificate in Business Analytics Busines Analytics Certification - upGrad Steps for Stakeholder Analysis with Examples Stakeholder Analysis is a very critical step for the success of a company. Here are the steps on how it can be achieved –  Identify the stakeholders The first step in stakeholder analysis is to identify all the individuals or groups that are affected by an organisation’s activities. This can include internal stakeholders like employees and shareholders and external stakeholders like customers, suppliers, community groups, and government entities.  For example, a software company might identify stakeholders such as employees, investors, customers, software developers, and government regulators. Prioritise the stakeholders Once all stakeholders are identified, they need to be prioritised based on their level of influence and interest in the organisation’s activities. This can be done by stakeholder mapping on a power/interest grid, where stakeholders with high power and high interest are considered key players, and those with low power and low interest are considered low priority.  For example, the software company might prioritise stakeholders like customers, investors, and software developers as key players and government regulators and community groups as a lower priority. Understand stakeholder needs and expectations Once stakeholders are prioritised, it is important to understand their needs and expectations. This can be done through interviews and surveys.  For example, the software company might conduct interviews with key customers to understand their expectations for software features and functionality. Evaluate stakeholder impact After understanding stakeholder needs and expectations, assessing the potential impact of the organisation’s activities on each stakeholder group is important. This can be done through a risk assessment or impact analysis.  For example, the software company might evaluate the potential impact of new software features on software developers and customer adoption. Read our Other Articles Related to Business Analytics What is Business Analytics? Career, Salary & Job Roles Top 7 Career Options in Business Analytics Business Analytics Free Online Course with Certification Business Analytics Vs Data Analytics: Difference Between Business Analytics and Data Analytics Top 7 Best Business Analytics Tools Recommended for every Business Analyst Top 11 Industry Applications of Business Analytics Future Scope of Business Analytics Business Analytics Eligibility or Requirement 8 Business Analytics Tips: Which Helps to Run Business Successfully Develop a stakeholder engagement plan Based on the stakeholder analysis, you can develop a stakeholder engagement plan that outlines how the organisation will engage with each stakeholder group. This plan should be tailored to meet the needs and expectations of each stakeholder group.  For example, the software company might develop a plan to engage with key customers through regular product updates and customer feedback surveys. Things to Avoid While lots of companies work to maintain relationships with their stakeholders, here are some things that must be avoided in the process –  Ignoring key stakeholders It is important to identify and prioritise all key stakeholders, including those who may not have direct influence or power but are still affected by the organisation’s activities. Stereotyping or making assumptions about stakeholders Avoid stereotyping or making assumptions about stakeholders based on their group affiliation or background. Each stakeholder should be considered as an individual with unique needs and perspectives. Failing to engage with stakeholders Stakeholder analysis should involve engagement and consultation with stakeholders to consider their perspectives. Avoid conducting the analysis in isolation without engaging with stakeholders. Neglecting to update the analysis Stakeholder analysis should be an ongoing process and updated regularly to reflect organisational or stakeholder environment changes. Overcomplicating the process Stakeholder analysis should be conducted clearly, concisely, and structured manner. Avoid overcomplicating the process with too many categories or complex frameworks that can lead to confusion or inaccuracies. Assuming stakeholder perspectives Avoid assuming stakeholders’ perspectives without engaging with them directly. The analysis should be based on stakeholder input and feedback rather than assumptions. Conclusion Organisations can gain insights into the potential impact of their activities on stakeholders by conducting a stakeholder analysis. They can develop tailored engagement strategies to address their needs and concerns. Through this process, organisations can build stronger relationships with stakeholders, mitigate risks, and make more informed decisions leading to profit generation. One best way to acquire proficiency in stakeholder analysis and other business processes is by upskilling in the field of business. With upGrad’s Master of Science in Business Analytics, learners can take a step towards exciting opportunities and growth! This course provides the required knowledge and skills demanded to tackle real-world business issues. Skills like statistical and analytical theories will be honed through the wide variety of subjects provided in this field. 

Have you ever worked on a project with unclear roles and responsibilities, causing confusion and delays? Many teams struggle with defining who is responsible for what, leading to inefficiencies.  Fortunately, there’s a solution: RACI.  RACI is a simple and powerful tool that helps teams clarify roles and responsibilities for specific projects. By using RACI, teams can streamline communication, improve collaboration, and achieve better project outcomes.  According to recent research, 80% of companies struggle with decision-making. This is where RACI comes in handy.  If you want to understand what is RACI in project management and how it can be used efficiently, read on.  What is a RACI Matrix? A RACI chart, also known as the responsibility assignment matrix (RAM), illustrates team members’ roles and responsibilities for specific tasks or projects. The acronym RACI stands for Responsible, Accountable, Consulted, and Informed, which are the four key roles that are assigned to individuals involved in a project. This helps ensure that everyone on the team understands their role and responsibilities, which can improve communication, collaboration, and project outcomes. Responsible (R): The person or people who are responsible for completing the deliverables. Accountable (A): The individual ultimately responsible for the success or failure of the deliverables. Consulted (C): The people who need to be consulted for input or feedback on the deliverables. Informed (I): The people who must be informed of progress or changes related to the deliverable consistently. How to create a RACI chart? Let’s discuss the step-by-step process of creating a RACI chart that will make help you streamline work better –  Step 1 – Identify the team members Identify the team members who will be involved in completing the project. This can include individuals from different departments or functions within the organisation. For example, project managers, software engineers, executive sponsors, etc.  Step 2 – Understand the project and milestones that need to be achieved Create a list of all the tasks or deliverables that must be completed for the project. This list should be as comprehensive as possible to ensure all responsibilities are accounted for. Step 3 – Create RACI rows and assign tasks  Determine which team member will be responsible, accountable, consulted, or informed for each deliverable. Assign roles to the project, like website designing, client approval, testing, and more.  Step 4 – Create a visual representation of a RACI chart Use a spreadsheet program such as Excel or Google Sheets to create a table with the tasks on the left-hand side and the team members at the top. Then, assign the appropriate RACI roles to each cell in the table. Step 5 – Discuss and review Once you have created the initial RACI chart, review it with the team members involved in the project to ensure that everyone agrees with their assigned roles and responsibilities. Make any necessary adjustments based on the feedback on the project plan. What to avoid when working with a RACI chart? Creating a RACI chart helps streamline the process. However, some things must be avoided –  Overcomplicating the chart It’s important to keep the RACI chart simple and easy to understand. Avoid adding unnecessary levels of detail or assigning too many roles to a single task, as this can lead to confusion and decrease the chart’s usefulness. Assigning multiple people as accountable Only one person should be accountable for each duty or deliverable in the RACI chart. Assigning multiple people as accountable can lead to confusion and a lack of accountability. Learn business analytics courses online from the World’s top Universities. Earn Masters, Executive PG Programmer Certification, or Global Master Certification to fast-track your career. Failing to update the chart The RACI chart should be updated regularly to reflect changes in the project, team composition, and other factors. Failing to update the chart can lead to outdated information and confusion about roles and responsibilities. Assigning too many people to the consulted or informed roles While it’s important to keep stakeholders informed and involved in the project, assigning too many people to the consulted or informed roles can lead to unnecessary delays and communication challenges. Using the RACI chart as a substitute for communication The RACI chart should be used as a tool to support communication and collaboration among team members rather than a substitute for direct communication. It’s important to have open and ongoing communication about roles and responsibilities throughout the project. Check out our free courses related to upskill yourself. How to implement RACI chart? E-mails are not the sole or most effective means of RACI implementation. Here are some key factors to consider –  The document should be reviewed All team members and stakeholders should attend a meeting early in the project schedule to examine critical documents; ideally, this meeting should occur at the project launch.  Get Feedback Send the paper to all attendees as read-ahead material and ask for feedback. By getting this early input, most changes can be made before the meeting, enabling a seamless presentation of the final RACI. Explore our Business Analytics Programs from World's Top Universities Business Analytics Certification Programme Busines Analytics EPGP - LIBA Professional Certificate Program in Data Science and Business Analytics Master of Science in Business Analytics Global Master Certificate in Business Analytics Busines Analytics Certification - upGrad Review the tasks Review the duties of every team member. Do not rush through this review; instead, allow enough time for this crucial component at the beginning of your project. Exploring the Advantages of Implementing RACI Chart RACI comes with a number of benefits for  Clarifying roles and responsibilities A RACI chart clearly defines who is responsible, accountable, consulted, and informed for each duty or delivery, which helps to avoid confusion, reduces misunderstandings, and ensures that everyone knows their role in the project. Improves communication and collaboration The RACI chart promotes communication and collaboration by clearly understanding who needs to be involved in each task or decision and to what extent. This helps ensure that everyone is informed, consulted, or involved as needed, leading to better decision-making and more effective collaboration. Increases accountability The RACI chart increases accountability by assigning clear ownership and responsibility for each task or deliverable. This helps ensure that tasks are completed on time and to the required standard, improving project outcomes. Helps to manage risks The RACI chart can help to identify potential risks by ensuring that all relevant stakeholders are involved in decision-making and that tasks are assigned to the appropriate person. This can help minimise the risk of errors or omissions, leading to project delays or failures. Improves project efficiency The RACI chart helps streamline project management by providing a clear and concise overview of roles and responsibilities, reducing the time and effort required for communication and decision-making. Read our Other Articles Related to Business Analytics What is Business Analytics? Career, Salary & Job Roles Top 7 Career Options in Business Analytics Business Analytics Free Online Course with Certification Business Analytics Vs Data Analytics: Difference Between Business Analytics and Data Analytics Top 7 Best Business Analytics Tools Recommended for every Business Analyst Top 11 Industry Applications of Business Analytics Future Scope of Business Analytics Business Analytics Eligibility or Requirement 8 Business Analytics Tips: Which Helps to Run Business Successfully Conclusion A RACI chart is a powerful tool that can help project managers clarify roles and responsibilities. By providing a clear and concise overview of roles and responsibilities, the RACI chart can help to streamline project management and facilitate decision-making. Whether you are managing a small project or a large-scale initiative, the RACI chart can be a valuable resource that can help you to achieve project success. While comprehending the know-how of a RACI chart can b greatly beneficial for organisational success, upskilling is another crucial aspect that every employee must consider! upGrad’s Global Master Certificate in Business Analytics is an excellent choice if you’re looking to enhance your skills in your field of interest. Provided under expert guidance from Michigan State University, candidates can learn the basics of using data to enhance corporate performance, quick decision-making, and long-term plan formulation. With hands-on experience, you will certainly become an imperative part of the business world, extending your skills and knowledge to benefit countless organisations.