Data Analyst Salary in India in 2024 [For Freshers & Experienced]

Updated on 21 May, 2024

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Data Analyst Salary in India

Table of Contents

  1. 2. Data Engineers
    1. Responsibilities of Data Engineers
      1. Data Engineer Salary Range in India
        1. 3. Data Analyst
          1. Data Analyst Responsibilities
      2. Data Analyst Salary in India
      3. Factors Affecting Data Analyst Salary in India
        1. Data Analyst Salary in India: Based on Experience
        2. Data Analyst Salary in India: Based on Industry
        3. Data Analyst Salary in India: Based on Location
        4. Data Analyst Salary in India: Based on Company
        5. Data Analyst Salary in India: Based on Skills
      4. Data Analyst Salary on Other Countries
      5. Salaries of Related Roles Compared to Data Analyst
      6. Data Analyst Salary: Tabular Overview
        1. Company-Based Data Analyst Salary
        2. Specialization-Based data analyst salary for freshers
        3. Experienced-Based starting salary of data analyst in India
        4. City-Based Data Analyst Salary
        5. Nation-Wise average salary of data analyst in India
      7. Key Reasons to Become a Data Analyst
        1. 1. Highly in-demand field
        2. 2. Highly Paid & Diverse Roles
        3. 3. Evolving workplace environments
        4. 4. Improving product standards
        5. 5. Helping the world
      8. Job Responsibilities of Data Analysts
      9. Myths Vs Reality
        1. Myth #1: Data analysts are the masters of Mathematics.
        2. Myth #3: Analytics won’t tell you anything you don’t already know.
        3. Myth #4: Your company isn’t big enough to need any analyses.
        4. Myth #5: You must report on every single metric.
      10. How should you kick-start a Career in Data Analytics?
        1. 1. Select the right role
        2. 2. Join a Science Diploma or certification course
        3. 3. Learn to code: choose a programming language.
        4. 4. Join Data Analysts community and forums
        5. 5. Enhance your communication skills
        6. 6. Focus on practical applications
      11. What Does The Future of a Data Analyst Looks Like?
      12. Conclusion
      13. Frequently Asked Questions (FAQs)
    2. Skills required to be a Data Engineer

Summary:

In this Article, you will learn about Data Analyst Salary in India in 2024.

Data Science Job roles Average Salary per Annum
Data Scientist ₹698,413 per year
Data Engineer ₹8,56,643 per year
Data Analyst ₹424,414 per year

Read more to know each in detail.

Wondering what is the range of Data Analyst salary in India?

Data Analysis become one of the most high-in-demand jobs around the world. As a result, a Data Analyst salary in India is significantly higher than other software related professionals. Check out our data science free courses to get an edge over the competition.

Data analysts use mathematical and analytical techniques to convert data into valuable insights that drive informed business decisions. As the volume of data accessible to organizations grows, the need for proficient data analysts to analyze and interpret it also increases.

Thus, if you have the required skillset and are ready to keep yourself updated, your career as a Data Analyst is expected to keep growing onwards and upwards. This line stands true especially when we consider that a data analyst salary in India is directly or indirectly dependent on how upskilled and updated they are.

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Cut short; we generate over 2.5 quintillion bytes of data each day.

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Demand for Data Analysts is on Rise

Naturally, this generates and adds to an ever-increasing pile of data, which brings forth the need for someone who could analyze huge heaps of data and help make sense of it.

Therefore, the buzz around a data analyst’s job role has increased significantly over the last few years. Of course, as you research what is data analyst and what the possible data analyst salary Pune, data analyst salary Delhi, data analyst salary Chennai, or data analyst salary Hyderabad could be, you might realize that the demand for the profile is immense. At least by the Indian job market standards.

Let’s take a look at who exactly is a Data Analyst and what is a typical data analyst salary in India?

Who is a Data Analyst & what do they do?

Data Analysts are professionals who translate numbers, statistics, figures, into plain English for everyone to understand. Join our fullstack development bootcamp course if you are interested.

Given the circumstances, there’s always an increasing scope for Data Analysts at the workplace, and it may be an excellent choice for those who have a strong foothold in mathematics, statistics, computer science or business backgrounds. This position includes data mining, fluency in languages like SQL, Python, etc. to extract the relevant insights from the data sets as well as channeling those ideas through visualizations and reports.

A Data Analyst collects, stores, and interprets data to transform it into valuable business insights that can be used to improve business operations and foster data-driven decision making. Since this job role involves parsing through data, analyzing it, and interpreting it, it is primarily analytical. The increasing demand for data analysts are increasing the data analyst salary in India.

Once Data Analysts are able to interpret the hidden information from within large datasets, they must be able to communicate that information effectively to all the stakeholders involved – colleagues, business & management teams, clients, company partners, etc. Because of the demand, data analyst salary in India is one of the highest.

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Skills required for the profile of a Data Analyst 

1. Solid Domain Understanding

Data Analytics skills help in problem-solving. They need to understand the variables in a business, the levers that they can potentially move to bring about a significant positive change, the external and internal factors that affect its growth, and model all necessary decisions accordingly. Business understanding is a must-have and one of the most critical skills if you aspire to become a data analyst and directly impacts the data analyst salary in India.

2. Analytical Skills

When it comes to analytical skills, a Data Analyst plays a crucial role in interpreting complex data. Your ability to transform this data into actionable insights is key to enhancing business operations. High analytical power allows you to discern patterns, trends, and relationships within the data, ultimately guiding strategic decision-making.

3. Mathematics & Statistics

Objective decision-making forms a very important part of how you arrive at the solution of any given decision. To be able to take decisions objectively you must rely on Mathematics and Statistics. You need to find patterns, segment, make predictions based on historical information. You will need to use prediction algorithms, classification, and clustering algorithms to arrive at the best possible solution, and that is where Mathematics and Statistics will come to the rescue.

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4. Technical Skills

You can identify and solve a problem using domain understanding and mathematical skills. But most businesses are not so simple. You will need to go through data sets that are way beyond your calculative abilities, and in order to be able to replicate your algorithms and business solutions at scale, it is very important that you pick up tools such as R, Python, SQL etc.

Must read: Data structures and algorithms free course!

5. Soft Skills

Last, but not the least of data analytics skills, you should be able to communicate your solution in the most simple and understandable format to the stakeholders. They might not know anything about KS Statistics, or root mean square error, or your clustering algorithm but that is where your soft skills come in. Impactful communication, use of great visualization, and visualization tools like Tableau, QlikView, ggplot, etc., become really important.

Our learners also read: Learn Python Online Course Free 

6. Problem-Solving Skills

As a Data Analyst, you need to have strong problem-solving skills. These skills will enable you to analyze numbers, trends, and data to draw meaningful conclusions. By doing so, you can provide valuable insights and effectively address complex business challenges. Developing and nurturing your problem-solving skills is crucial for success in this field.

Data Analyst Job Roles

1. Data Scientists

Data science is basically statistics implemented through programming. Alongside R, Python has also shown its mettle in sorting out data as per generic as well as specific requirements. As far as India is concerned, Python programmers for data science earn more than both software developers as well as DevOps programmers. The reason for this is that data collection, data cleaning and processing is becoming very common nowadays as companies need data to gather market and customer information.

This requires a niche of Python programmers who are specially trained in the collection and processing of data through libraries like NumPy and Pandas. Data scientists are in high demand in major metros like Delhi-NCR and Mumbai and emerging cities such as Pune and Bangalore.

Responsibilities of Data Scientists

  • Gathering vast amounts of structured and unstructured data and converting them into actionable insights.
  • Identifying the data-analytics solutions that hold the most significant potential to drive the growth of organizations.
  • Using analytical techniques like text analytics, machine learning, and deep learning to analyze data, thereby unravelling hidden patterns and trends.
  • Encouraging data-driven approach to solving complex business problems.
  • Cleansing and validating data to optimize data accuracy and efficacy.
  • Communicating all the productive observations and findings to the company stakeholders via data visualization.

Data Analyst Qualification Requirements

  • A bachelor’s or graduate degree in computer science, business, engineering, or information systems, or relevant work experience, is required. 
  • A time manager with leadership and analytical skills.
  • Capable of working with datasets, statistics, and machine learning tasks. 
  • A strong capacity for critical thought and attention to detail. 
  • Possesses expertise in consulting and the capacity to offer support for problem-solving and debugging. 

Scope for Data Analyst Job in India

Every industrial niche focuses on using big data, leveraging it to make crucial decisions for its business and people. The power that analytics contains is waiting to be tapped by end-users such as businesses of all domains. There could be varied scales of businesses involved in exploring the power of data and analytics. This also implies a lot of opportunities in the making for job creation. The forecast is that the demand for the role of what is data analyst profile outweighs the present supply for the same.

5 Reasons why Start-ups Are Fuelling Data Analysis Growth

In India alone, the role of a data analyst is not limited to specific niches. However, the demanded skill set for such a role is very specific and thereby, finding a space in the freshly run start-ups. Even from the perspective of the hiring authority, the focus remains on tapping a pool with the specific skill sets needed for data analyst roles. This naturally widens the candidate pool for such jobs and influences the data analyst salary Pune, data analyst salary Delhi, data analyst salary Chennai, or data analyst salary Hyderabad among other places. Here are a few reasons why data analyst role and salary are experiencing a growth.

  1. India is a hub for start-ups and is seeing a massive increment in the number of enterprises operating in this big data analytics space. 
  2. These start-ups are gradually observing funding and an influx of growth significantly. The boom for such start-ups has contributed substantially to the demand for data analysts, which is set to peak further.
  3. Considering that companies in India realize the power and opportunities associated with data analysis, a considerable investment is anticipated in this context. 
  4. Data analytics is a sort of growth trigger, and this is enhancing the demand for data analytics training. 
  5. Another factor contributing to the demand for data analysts’ jobs is the salary and the absolute need for such profiles in e-commerce companies.

Only the expertise of qualified data analysts can help such companies derive insights into the data they handle. Additionally, this will steadily open up more opportunities for revenue enhancement too!

Data Scientists Salary Range in India

Data scientists in India can earn varying salaries based on their experience and skill level. The average data scientist’s salary is ₹713,180. For those just starting in the field, an entry-level data scientist can make around ₹398,000 per year with less than a year of experience. As you gain 1 to 4 years of experience, your salary can increase to around ₹607,000 annually.

With 5 to 9 years of experience as a mid-level data scientist, your earning potential can rise to ₹1,004,082 per year. However, it’s important to note that your salary can increase significantly as you continue to grow your experience and skills. Senior-level data scientists in India make over ₹2,000,000 per year! 

So, as you progress in your career as a data scientist, your earnings have the potential to skyrocket.

The average data scientists salary is ₹698,413. An entry-level data scientist can earn around ₹500,000 per annum with less than one year of experience. Early level data scientists with 1 to 4 years experience get around ₹610,811 per annum.

A mid-level data scientist with 5 to 9 years experience earns ₹1,004,082 per annum in India. As your experience and skills grow, your earnings rise dramatically as senior-level data scientists around more than ₹1,700,000 a year in India!

2. Data Engineers

The primary job of a Data Engineer is to design and engineer a reliable infrastructure for transforming data into such formats as can be used by Data Scientists. Apart from building scalable pipelines to covert semi-structured and unstructured data into usable formats, Data Engineers must also identify meaningful trends in large datasets. Essentially, Data Engineers work to prepare and make raw data more useful for analytical or operational uses. There are many myths about data engineers and most of them are far from reality.

In an organization, the position of a Data Engineer is as vital as that of a Data Scientist. The only reason why Data Engineers remain away from the limelight is that they have no direct link to the end product of the analysis.

Responsibilities of Data Engineers

  • Integrate, consolidate, and cleanse data collected from multiple sources.
  • Prepare raw data for manipulation and predictive/prescriptive modeling by Data Scientists.
  • Develop the necessary infrastructure for optimal extraction, transformation, and loading of data from disparate sources using SQL, AWS, and other Big Data technologies.
  • Deploy sophisticated analytics programs, machine learning algorithms, and statistical techniques to build data pipelines.
  • Assemble vast and complex data sets to cater to the functional and non-functional business requirements.
  • Identify and develop innovative ways to improve data reliability, efficiency, and quality.
  • Develop, construct, test, and maintain data architectures.

Skills required to be a Data Engineer

  • Active project management and organizational skills.
  • Strong analytic skills to handle and work with large, unstructured datasets.
  • Strong programming flair in trending languages, including Python, Java, C++, Scala, Ruby, etc.
  • Advanced working knowledge of SQL, along with experience in working with relational databases.
  • Proficiency in working with a wide variety of databases.

Data Engineer Salary Range in India

According to Glassdoor, the average Data Engineer salary in India is Rs.8,56,643 LPA. But of course, the Data Engineer salary depends on several factors, including company size and reputation, geographical location, education qualifications, job position, and work experience. Reputed companies and big players in the Big Data industry like Amazon, Airbnb, Spotify, Netflix, IBM, Accenture, Deloitte, and Capgemini, to name a few, usually pay high compensation to Data Engineers. Also, the more your past work experience in Big Data, the higher will be your market value.

Despite the global demand-supply paradox (the demand for Data Engineers far exceeds their supply), the career prospect of Data Engineers looks promising in India. According to Analytics India Magazine report,

“While IT firms have shown a negative trend, the demand for data engineering professionals has increased across the companies, resulting in a significant jump in their salary structure. Whereas for salaries across analytics skills, advanced analytics roles and predictive modeling professionals grabbed the limelight compared to other roles.”

As for Data Engineers in their early career (1-4 years of experience), they make anywhere around Rs.7,37,257 LPA. As they proceed to mid-level (with 5-9 years of experience), the salary of a Data Engineer becomes Rs.1,218,983 LPA. Data Engineers having over 15 years of work experience can make more than Rs.1,579,282 LPA.

Source
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Data engineers in India have a range of job roles and paths for career advancement. Starting as an Associate Data Engineer or Data Engineer II, individuals with 2 to 4 years of experience can earn an average annual salary ranging from ₹7.7L to ₹9.1L. As they progress to become a Senior Data Engineer (or Data Engineer III), with an 80% advancement rate, those with 2 to 4 years of experience can earn ₹10L to ₹23L annually.

To further advance their career, they can aim to become a Lead Data Engineer, which typically requires 5 to 7 years of experience and offers an average annual salary between ₹19L and ₹33L. For highly experienced professionals with 8 or more years of experience, there are roles like Principal Data Engineer (₹26L – ₹44L), Senior Principal Data Engineer (₹34L – ₹39L), and Director of Data Engineering (₹42L – ₹49L) available, illustrating the progression opportunities in this field.

Data Engineer Salary Range in India

City Salary
Bangalore ₹ 11.2 Lakhs
New Delhi ₹ 11.1 Lakhs
Mumbai ₹ 10.0 Lakhs
Hyderabad ₹ 10.6 Lakhs
Pune ₹ 9.9 Lakhs
Noida ₹ 10.3 Lakhs
Gurgaon ₹ 12.5 Lakhs
Chennai ₹ 10.4 Lakhs

3. Data Analyst

Data Analysts are professionals who translate numbers, statistics, figures, into plain English for everyone to understand.

Given the circumstances, there’s always an increasing scope for Data Analysts at the workplace, and it may be an excellent choice for those who have a strong foothold in mathematics, statistics, computer science, or business backgrounds. This position includes data mining, fluency in languages like SQL, Python, etc. to extract the relevant insights from the data sets as well as channeling those ideas through visualizations and reports. Lets deep dive into data analyst responsibilities and data analyst salary in India.

Data Analyst Responsibilities

  • To analyze and mine business data to identify correlations and discover valuable patterns from disparate data points.
  • To work with customer-centric algorithm models and personalize them to fit individual customer requirements.
  • To create and deploy custom models to uncover answers to business matters such as marketing strategies and their performance, customer taste, and preference patterns, etc.
  • To map and trace data from multiple systems to solve specific business problems.
  • To write SQL queries to extract data from the data warehouse and to identify the answers to complex business issues.
  • To apply statistical analysis methods to conduct consumer data research and analytics.

Data Analyst Salary in India

For a data analyst in India, having 1 – 4 years of experience has a gross earning (including tips, bonus, and overtime pay) of Rs 3,96,128, while a mid-career Data Analyst with 5 – 9 years of experience can make up to Rs 6,03,120 based on the organization and the location of the working place. And if you are a matured and experienced Data Analyst who has been in the industry or 10 – 19 years can earn an average total compensation of Rs 9,00,000.

Source

– 78% of the analytics professionals in India are under the salary bracket of 0 – 6 Lakhs at their entry level, but since there has been a rise in the number of freshers in Data Analysis in India, this is an excellent indication for maturing the industry. Data Analyst salary in India is affected by multiple elements like location, skills, experience and company.

– The salaries for 4 – 6 years of experienced remain stable at 8.7 Lakhs.

– For the Senior Data Analyst having substantial experience of 12 or more years has witnessed a sharp 20% rise in their salaries last year.

So how much does a data analyst earn in India? Based on Payscale, here’s a breakdown of the average Data Analytics salary at different stages of their careers:

  1. Entry-Level (less than 1 year of experience): ₹402,820
  2. Early Career (1-4 years of experience): ₹494,209
  3. Mid-Career (5-9 years of experience): ₹775,162
  4. Late Career (10-19 years of experience): ₹1,063,150
  5. (Experienced20 years and higher): ₹1,500,000

These figures include various elements like tips, bonuses, and overtime pay.

The companies across the world are thoroughly valuing analytics and its potential in changing the market trends, leading the decision-makers of the companies to invest more and more in the technology, people, and processes. This has led to the shift of Data analytics from I.T. and finance to most business functions. The reports by the U.S. Bureau of Labor Statistics indicates that the Data Analysts are projected to see faster than average growth of 19% from 2014-2024, thanks to the continuous growth of data generation and the need to refine and extract relevant insights from the same.

Data Analyst Salary in India Experience Wise

Experience Salary
1 Year ₹4.6 Lakh
2 Year ₹5.3 Lakh
3 Year ₹6.0 Lakh
5 Year ₹7.7 Lakh
6 Year ₹8.2 Lakh

Data Analyst Salary in India Industry-Wise

Industry Salary
IT Services ₹6.1 Lakh
Internet ₹7.5 Lakh
Software Product ₹6.8 Lakh
Financial Services ₹7.1 Lakh
KPO ₹7.1 Lakh

So, the next question that arises is: what are all the factors affecting data analyst salary in India?

Factors Affecting Data Analyst Salary in India

Data Analyst salary in India can be affected by multiple factors. Let’s see some primary salary affecting factors:

  1. Experience
  2. Industries
  3. Location
  4. Company
  5. Skills

Data Analyst Salary in India: Based on Experience

Data analytics can yield your earnings, which are well above the median of $47,000 for a full-timer in the U.S., but it is subjective from one organization to another based on the years of experience.

According to Zippia, the average entry-level business/data analyst salary having 2 years of experience and a bachelor’s degree is $54,000 which can rise to $70,000 in just 2 to 4 years of experience in the USA. Generally, a senior analyst with more than 6 years of experience commands a higher salary of about $88,000 but, with a specialization in the field can make the salary can soar as high as $100,000.

Let’s see how Data Analyst salary in India varies based on experience.

Entry-Level Data Analyst Salary in India

The average salary of entry-level Data Analyst salary in India is ₹325,616.

Mid-Level Data Analyst Salary in India

The average salary of a mid-level Data Analyst salary in India is ₹635,379.

Experienced Data Analyst Salary in India

The average salary of an experienced Data Analyst salary in India is ₹852,516.

Let’s see how the salary increases with experience:

Source

While the data analyst salary in 2022 can increase steadily over the first five to 10 years, afterward it would prove to be increasingly challenging to obtain raises without working on broadening of your skills. Therefore, many data analysts who are unable to work up their ways to success end up in switching their careers as the critical difference of data scientists to that of data analysts lies to the former’s superior knowledge in advanced programming, data modeling, machine learning and more leading them to have a higher pay to that of data analysts.

As mentioned before, data scientist job openings and payments are subjective from one organization to another leading many data analysts to perform in the scope of the work of the data scientists according to the company’s requirements. It is, therefore, better to understand the scope and details of the work before you can choose your work scenario in such places.

Data Analyst Salary in India: Based on Industry

Data analytics now run in the very foundation of every industry, and due to that, there has been a remarkable increase for the data analysts in the number of paths to choose from as it adds a lot of value and enhances the industries to make steady progress in their respective genres.

This progress can impact directly to the data analyst salaries as these people are directly responsible for some of the decision-making processes for the organization with the help of data extracted and analyzed using the tools like Excel, Tableau, and SQL. Their salaries can range from $54,700 to $69,000 at the entry level.

Data Analysts Salary Trends in India By Industry

For the financial analysts who work with the financial accounts of the company to predict its performance and study the macro and microeconomic trends, creating economic models and forecasts. According to the 2017 Robert Half Salary Guide, the financial analysts at an entry-level can make up to $52,700 to $66,000 based upon bonuses and commissions.

Market research analysts also use sales, competitor research, and customer survey data to design the landscape for a product to optimize the segmentation, targeting, and positioning efforts. Such useful insights need a strong skill of communication, compelling storytelling, and a very refined quantitative data analysis – calling for significant pay at the starting level ranging from $51,000 to $65,000.

Also read: Data Scientist Salary in India

Similarly, for the data analysts in the healthcare industry manage analytics within the hospital settings to streamline the daily administrative workflow and operations. The salary for these individuals may range from $46,000 to $80,000 and can come with branch or stream specifications as well.

In India, various sectors offer competitive salaries for data analysts. Financial services provide an average annual salary of ₹8.1 LPA, while the internet industry offers ₹6.8 LPA. Management consulting firms compensate data analysts with an average of ₹7.3 LPA, whereas software product companies provide ₹6.3 LPA. IT services and consulting sectors offer ₹5.8 LPA for data analysts. Analytics and KPO companies offer an average salary of ₹6.1 LPA, while BPO/KPO companies compensate the highest salary of data analysts in India with ₹9.0 LPA. Overall, the data analyst salary in India varies across different industries, reflecting the growing demand for professionals in the field of data analytics.

Now that you’re well aware of the salary systems for data analysts and how it works in the industries, the next thing you need to know is,

Data Analyst Salary in India: Based on Location

Let’s see how data analyst salary in India gets affected by the location.

Data Analysts in Bangalore, Karnataka, have an average salary of 18.8% higher than the national average. Similarly, job titles in Gurgaon, Haryana, and Hyderabad, Andhra Pradesh, also command higher than average salaries, with an increase of 18.5% and 9.4%, respectively. On the other hand, the lowest salaries are observed in Mumbai, Maharashtra (4.8% below average), Pune, Maharashtra (1.9% below average), and Chennai, Tamil Nadu (1.3% below average).

Source

The number of job opportunities and the annual data analyst salary in India for data innovators is the highest in Bangalore. The Silicon Valley on India provides 19.2% more than the country’s average. Gurgaon & Pune offers 9.8% more and 9.5% respectively than the national average. Data Analysts from Mumbai, Hyderabad, and New Delhi receives 5.2%, 4.8% and 2.8% lesser than the national average respectively.

Data Analyst Salary in India: Based on Company

Let’s see how data analyst salary varies on companies

Source

For the Data Analyst titles, employers like Accenture, Tata Consultancy Services and Ernest & Young (E.Y.) are some of the top respondents. However, the reported salaries are highest at HSBC, making the average pay to be at Rs. 6,83,000.

According to Payscale, the companies employing the most data analysts are Tata Consultancy Services Limited, Accenture, and Amazon.com Inc. Among these companies, Accenture pays the highest average salary, which is ₹592,183. Deloitte and Accenture Technology Solutions also offer competitive salaries, averaging around ₹591,152 and ₹540,646, respectively.

On the other hand, Amazon.com Inc. pays the lowest salary at around ₹427,040. Capgemini and Tata Consultancy Services Limited have relatively lower salaries, paying ₹427,500 and ₹447,045, respectively.

Data Analyst Salary in India: Based on Skills

The salary of a Data Analyst in India varies significantly based on the individual’s skills and expertise. According to available data, professionals proficient in data quality experience a notable salary increase of around 219%. Additionally, expertise in tools like Qlik Sense and Big Data Analytics can contribute to salary increments of 108% and 89%, respectively. Proficiency in Business Intelligence and Teradata can also result in salary growth of around 89% and 79%, respectively.

Moreover, professionals skilled in the Snowflake Cloud Data Platform and JavaScript see a salary increase of approximately 64%. Furthermore, expertise in ETL (Extract, transform, load) and Splunk can boost salaries by around 63% and 49%, respectively. Finally, Web Analytics skills contribute to an increase of around 49% in data analyst salaries.

In order to secure such a high-paying job, you are expected to go beyond the qualifications of a Master’s degree and be familiar with the respective languages and software utilized for managing data. Some more insights from AIM:

  • The very essential skill is being familiar with Python. Python salary in India alone offers ₹10 Lakhs per annum.
  • When you are familiar with Big Data & Data Science, data analyst salary in India increases by 26% compared to being skilled in only one of the areas.
  • SPSS experts can earn around ₹7.3 lakhs where SAS professionals are earning between ₹9 to 10.8 lakhs.
  • Machine Learning salary in India can increase up to 17 lakhs per annum. When you learn ML and Python, it is among one of the highest you can get in this field.

Source

So, now is the time to master your skills in data in order to further optimize your salary!

Data Analyst Salary on Other Countries

Let’s see how the data analyst salary is in different countries.

Data Analyst salary in The US: $66,000

Source

Data Analyst salary in The UK: £26,000

Source

Salaries of Related Roles Compared to Data Analyst

Let’s look at the average salaries of related roles compared to Data Analyst salary in India.

Software Engineer average annual salary in India: ₹514,537

Business Analyst average annual salary in India: ₹607,736

Data Scientist average annual salary in India: ₹813,042

Python Developer average annual salary in India: ₹555,776

ML Engineer average annual salary in India: ₹956,000

Source

Data Analyst Salary: Tabular Overview

Company-Based Data Analyst Salary

How much does a data analyst earn in India? Following course completion, top companies with excellent compensation and perks hire Data Analysts. Here is a table that illustrates the typical yearly salary for a data analyst salary fresher in India in various firms. 

Company Hiring Data Analysts  Average Data Analyst Salary 
Amazon INR 8.60 L
Accenture INR 5.85 L
Infosys INR 5.20 L
Ernst & Young  INR 5.59 L
IBM INR 5.94 L
Google  INR 13.20 L
Tata Consultancy Services INR 6.51 L
Cognizant  INR 5.40 L
Deloitte  INR 6.05 L
Wipro INR 5.00 L

Specialization-Based data analyst salary for freshers

Candidates can choose to specialize in order to pursue a job as a data analyst while still in college. They are employable in a variety of fields, such as finance, healthcare, and insurance. Here is a table representing the average yearly Data Analyst Salary based on their specialization.

Specialization  Average Data Analyst Salary 
Healthcare Analyst INR 4.67 L
Social Media Data Analyst INR 3.30 L
System Analyst INR 6.60 L
Financial Analyst  INR 5.01 L
Database Engineers INR 6.00 L
Insurance Underwriting Analyst INR 5.20 L

Experienced-Based starting salary of data analyst in India

Here is a salary breakdown for data analysts based on years of experience. 

Experience  Average Data Analyst Salary 
0 – 5 years INR 3.60 L
6 – 10 years INR 5.50 L
11 – 15 years INR 7.90 L
16 – 20 years INR 12.40 L
20 years & above INR 16.10 L

City-Based Data Analyst Salary

Any career’s pay is also influenced by the city an applicant is from. Candidates from major cities will almost usually receive a better deal than candidates from rural areas. The Data Analyst’s Salary for various cities is shown below for your reference. 

City Average Data Analyst Salary 
Gurugram INR 5.16 L
Hyderabad INR 5.70 L
Bangalore INR 5.59 L
Delhi INR 6.08 L
Mumbai INR 6.15 L
Noida INR 5.26 L
Hyderabad INR 5.70 L

Nation-Wise average salary of data analyst in India

Since it offers a wider viewpoint, significantly higher pay, and numerous employment options on a worldwide scale, students frequently seek to pursue further education at foreign universities. The UK, USA, Australia, and Canada are a few of the contenders’ top picks. For your reference, the average Data Analyst Salary for various nations is listed below. 

Nation Average Data Analyst Salary 
United Kingdom INR 49.30 L
United States INR 45.47 L
Canada INR 30.10 L
Australia INR 30.85 L
Germany INR 37.20 L

Key Reasons to Become a Data Analyst

1. Highly in-demand field

Data Analysis is one of the most in-demand jobs for 2024. After United States, India is the second prominent hub of jobs for data scientists. Demand is one of the reason data analyst salary is significantly high.

2. Highly Paid & Diverse Roles

Not only is the demand for data scientists booming, but the kinds of job positions are also abundant.

3. Evolving workplace environments

Data science is shaping the workplace of the future. With the advent of artificial intelligence and robotics, more and more routine and manual tasks are getting automated.

4. Improving product standards

Usage of machine learning has enabled companies to customize their offerings and enhance customer experiences.

5. Helping the world

Predictive analytics and machine learning have revolutionized the healthcare industry.

Job Responsibilities of Data Analysts

  1. Analyzing Trends and Patterns: Data Analysts have to predict and forecast what may happen in the future, which could be very helpful in strategic decision making to the businesses. In this case, a data analyst has to spot the trends that have happened over time. He also has to make specific recommendations by analyzing the patterns.
  2. Creating and Designing Data Report: The reports given by a data scientist is the essential prerequisite in the decision making of a company. Data scientists will need to create the data report and design it in such a way that it is very easily understandable by the decision-maker. Data can be represented in many ways like pie-charts, graphs, charts, diagrams and many more. Reporting of Data can also be done in the form of a table depending on the nature of data to be shown.
  3. Deriving valuable insights from the Data: The Data Analysts will need to derive useful and meaningful insights from the package of Data to bring some benefits to the organizations. The organization will be able to use those meaningful and unique insights to make the best decision for the success of their company.
  4. Collection, Processing, and Summarizing of Data: A Data Analyst has first to collect the data and then process it using the required tools and then summarize the data to be easily understood. The summarized data can tell a lot about the trends and patterns which will be used to predict things and forecasting. Data Analyst salary in India depends on all the responsibilities being fulfilled.

Myths Vs Reality

Let’s take a step forward and bust some myths revolving around the lives of a data analyst:

Myth #1: Data analysts are the masters of Mathematics.

This might have been true at one point of time, but now with much more sophisticated tools entering the market, there are more opportunities than ever for people who don’t have a math background to learn about analytics.

Myth #2: Analytics takes a lot of time.

Most of the organisations opt against data analytics thinking it’ll take too much of time and they’ll be left with little time to do the actual work. However, that’s seldom the case. Once you figure out the metrics, you should be keeping an eye on, and how to track them in your tools, it’s pretty quick to measure those metrics. You will know precisely where to pull those and how to make changes to your operations based off of those metrics.

Myth #3: Analytics won’t tell you anything you don’t already know.

Just because you think you can guess the fate of your campaign does mean it’s necessarily true. Every time your organisation runs any campaign, the data analyst analyzes the type of content and channels that are performing well.

Myth #4: Your company isn’t big enough to need any analyses.

Any company, however big or small, can overhaul their operations using data analytics. Especially for smaller organisations, data analytics can come in extremely handy to understand how to grow — and to find out whether you are growing in the desired direction. It also helps you track visitor-to-lead conversion rates and lead-to-customer conversion rates; which helps in understanding if there’s an area of the funnel that is not working and helps you decide what to focus on.

Myth #5: You must report on every single metric.

Well, this is entirely up to you. If you want, you can spend 100% of your time reporting on every single metric you can find. There is an endless amount of data, and you can go on creating metrics for analyzing – it’ll take you to an infinite loop.

How should you kick-start a Career in Data Analytics?

1. Select the right role

As stated above, the data science field is very diverse, with never-ending opportunities. You must have a strong understanding of current technology trends, how data analysts drive business decisions, tools in demand, and how data science can shape the future to get a good grasp of what you do and evolve with the organization you work for.

Staying in touch with key stakeholders, top management will help you achieve the same. Do not hesitate to ask the right question to understand the different roles of a data analyst. This will help you in deciding the role that suits best to your skill set and requirements.

2. Join a Science Diploma or certification course

Understand the role that you need to perform and take appropriate guidance and mentorship from experts in this field. You must keep your skills and knowledge up-to-date with the role you need to perform. Take a step further and go for the PG diploma or certification courses to better perform your duties and strengthen your knowledge.

3. Learn to code: choose a programming language.

You must master a programming language to become an expert in data analysis. Python and R are the most popular languages. Select the language that you are comfortable with and learn until you have good command over it.

4. Join Data Analysts community and forums

This is one of the most important steps but often overlooked. You must join a data science forum, community group, or take active participation in technical discussions to know what is happening around, how data analysis is shaping the business goals, etc.

5. Enhance your communication skills

What if you have humongous knowledge but have no idea of conveying the same to others. Watch videos or take courses to enhance your presentation and communication skills. Learn different tools to present your findings conveniently and intuitively to the key stakeholders of the organization.

Also visit upGrad’s Degree Counselling page for all undergraduate and postgraduate programs.

6. Focus on practical applications

Don’t just read theory, also put the knowledge to test. Start developing applications that can do your work in less time and collate data from multiple sources with less coding. You can also take a few freelancing projects to work on different datasets.

What Does The Future of a Data Analyst Looks Like?

Businesses must take precautions to prevent the deterioration of their data. Continuous updates, awareness, and comprehension of a vast amount of data are necessary for this. 

Data analytics experts have become an integral part of the business model modification process as their absence can put the organization one step behind the competitors. From telecommunications and healthcare to eCommerce and banking, the need for data analytics is everywhere in the Indian sector. 

Prominent entities such as Microsoft, Wipro, Accenture, AIG, Deloitte, JPMorgan Chase, Ernst & Young, Adobe, Flipkart, and Vodafone are testament to the growing need for data analysts. These organizations invest heavily in data analytics, reflecting a broad trend toward data-driven decision-making processes.

Looking ahead, the future of the data analyst role is bright and buoyed by the continued digitalization of business processes. As more companies adopt data-centric models, demand for data analysts will only rise. However, alongside opportunities, this shift brings challenges. Data analysts will need to continually adapt and expand their skills to navigate the evolving landscape of data analytics.

They will need to master new tools and techniques, understand complex data structures, and develop the ability to translate data insights into actionable business strategies. While promising, the future of a data analyst will require continuous learning and adaptation to the rapidly changing data landscape.

Many organizations, including Microsoft, Wipro, Accenture, AIG, Deloitte, JPMorgan Chase, Ernst & Young, Adobe, Flipkart, and Vodafone have numerous jobs for data analysts.

Conclusion

Despite few IT firms showing a negative trend in the data analysts salaries, the demand for efficient data scientists and analysts seem to be on the rise and is inevitable, thanks to the ever-increasing amount of data online and the competitive market. As for the salaries across the analytical and predictive modeling skills, R remains to be the most in-demand with the highest salaries, followed closely by Python.

The opportunities for Data Analytics are currently at their prime in India. With the large volumes of data being generated by businesses and the availability of data and tools to extract it – and the urge to gain insights from it. It includes the rise in Data Analyst’s salary and Data Scientists salary India.

We hope you liked our article on Data Analyst salary in India. These numbers above are not set in stone. The real influencer of your salary is the skills you have,  the mastery you have attained over them, and how quickly you grow and make the company grow as well.

You are likely to receive an annual bump up of around 15% in your salary. This will further increase with an increase in the years of work experience and the number of skills you’ve mastered. Therefore, whether you’re starting from scratch or you’re already experienced in the field of data. You’ll always have this motivating factor driving you in your career!

If you are curious about learning data science to be in the front of fast-paced technological advancements, check out upGrad & IIIT-B’s Executive PG Program in Data Science.

Frequently Asked Questions (FAQs)

1. Is it worth learning data analytics?

If you are related to the tech world, there is no way you do not understand the importance of the word “data”. The world is nothing without data and hence we need someone who can play with it and get something useful out of it. This is where a data analyst comes into the picture.
Data analytics is hands down among the top trending fields and is high-paying as well. An average data analyst earns up to $72,250 per year which is pretty amazing. So, we can deduce that learning data analytics is totally worth it as it is in demand and pays you well too.

2. Where can I learn Data Analysis from basic to advance?

The following are the top data analysis courses in the industry that will help you to learn Data analysis from the scratch: IBM Data Analyst Professional Certificate - This is a beginner-friendly course that teaches all the foundational skills required to be an entry-level data analyst. IBM Data Analytics with Excel and R Professional Certificate - This course is a part of the 9-course certification courses of IBM Data analytics courses that highly focuses on Excel skills and Statistical R programming language. Google Data Analytics Professional Certificate - This is a beginner-level certification course from the tech giant Google itself. Specialized for junior and associate analysts, this course has all the foundational skills along with the practical applications of the latest data analytics tools.

3. What are the necessary skills to become a data analyst?

Data analytics is one of the most trending fields out there. But to master it, there are certain skills that you must learn beforehand. The following are the necessary skills that one must have in its arsenal to become a full-fledged data analyst: Analytical skills and mathematical skills, Critical Thinking, Statistical Programming Languages like R and Python, Database Management Skills- SQL, MySQL, and MongoDB, Data Visualization and presentation skills, Other data-related skills like machine learning and data mining, Hands-on knowledge of Microsoft Excel, Word, and PowerPoint.

4. What is the Entry level data analyst salary in India?

The entry-level data analyst salary in India is typically around ₹3 lakh to ₹5 lakh per year.

5. What is the Data analyst salary in India per month?

The data analyst salary in India per month is approximately ₹25,000 to ₹65,000.

6. What is the Data analyst salary per month in India?

The data analyst salary per month in India is approximately ₹25,000 to ₹65,000.

7. What is the Senior data analyst salary in India?

The senior data analyst salary in India ranges from ₹8 lakh to ₹15 lakh per year.

Did you find this article helpful?

Shaheen Dubash

Shaheen is a Content Marketing intern at UpGrad. Shaheen is currently studying at the University of Warwick. She is majoring in BSc Economics with a minor in Politics and International Studies. She completed her high school at the United World College of South East Asia in Singapore and JB Petit High School for Girls in Mumbai.

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Be open to other forms of compensation – There are plenty of non-monetary ways to entice Quants to your company, like having the latest tools, solving challenging problems, organization-wide buy-in for analytics and more. Other things to consider could be flexible work arrangements, remote options or other unique perks. Pick up the pace – Talented analytics professionals are rare, and the chances that qualified candidates will be interviewing with multiple companies are very high. Don’t hesitate to make an offer if you find what you’re looking for at a swift pace – your competitors won’t. Court the candidate – Just as you want a candidate who stands out from the pack, a candidate wants a company that makes an effort to stand apart also. I read somewhere, a client from Chicago sent an interviewing candidate and his family pizzas from a particularly tasty restaurant in the city. I can’t say for sure that the pizza was what persuaded him to take the company’s offer, but a little old-fashioned wooing never hurts. Button up the process – Just as it helps to have an expedited process, it also works to your benefit is the process is as smooth and trouble-free as you can make it. This means hassle-free travel arrangements, on-time interviews, and quick feedback. Network – make sure that you know the best of the talent available in the market at all levels and keep in touch with them thru porfessional social sites on subtle basis as this will come handy in picking the right candidate on selective basis Redesigned Interview Process In the old days one would screen resumes and then schedule lots of 1:1’s. Typically people would ask questions aimed at assessing a candidate’s proficiency with stats, technicality, and ability to solve problems. But there were three problems with this – the interviews weren’t coordinated well enough to get a holistic view of the candidate, we were never really sure if their answers would translate to effective performance on the job, and from the perspective of the candidate it was a pretty lengthy interrogation. So, a new interview process need to be designed that is much more effective and transparent – we want to give the candidate a sense for what a day in the life of a member on the team is like, and get a read on what it would be like to work with a company. In total it takes about two days to make a decision, and there be no false positives (possibly some false negatives though), and the feedback from both the candidates and the team members has been positive. There are four steps to the process: Resume/phone screens – look for people who have experience using data to drive decisions, and some knowledge of what your company is all about. On both counts you’ll get a much deeper read later in the process; you just want to make sure that moving forward is a good use of either of both of your time. Basic data challenge – The goal here is to validate the candidate’s ability to work with data, as described in their resume. So send a few data sets to them and ask a basic question; the exercise should be easy for anyone who has experience. In-house data challenge – This is should be the meat of the interview process. Try to be as transparent about it as possible – they’ll get to see what it’s like working with you and vice versa. So have the candidate sit with the team, give them access to your data, and a broad question. They then have the day to attack the problem however they’re inclined, with the support of the people around them. Do encourage questions, have lunch with them to ease the tension, and check-in periodically to make sure they aren’t stuck on something trivial. At the end of the day, we gather a small team together and have them present their methodology and findings to you. Here, look for things like an eye for detail (did they investigate the data they’re relying upon for analysis), rigor (did they build a model and if so, are the results sound), action-oriented (what would we do with what you found), and communication skills. Read between the resume lines Intellectual curiosity is what you should discover from the project plans. It’s what gives the candidate the ability to find loopholes or outliers in data that helps crack the code to find the answers to issues like how a fraudster taps into your system or what consumer shopping behaviors should be considered when creating a new product marketing strategy. Data scientists find the opportunities that you didn’t even know were in the realm of existence for your company. They also find the needle in the haystack that is causing a kink in your business – but on an entirely monumental scale. In many instances, these are very complex algorithms and very technical findings. However, a data scientist is only as good as the person he must relay his findings to. Others within the business need to be able to understand this information and apply these insights appropriately. Explore our Popular Data Science Courses Executive Post Graduate Programme in Data Science from IIITB Professional Certificate Program in Data Science for Business Decision Making Master of Science in Data Science from University of Arizona Advanced Certificate Programme in Data Science from IIITB Professional Certificate Program in Data Science and Business Analytics from University of Maryland Data Science Courses Good data scientists can make analogies and metaphors to explain the data but not every concept can be boiled down in layman’s terms. A space rocket is not an automobile and, in the brave new world, everyone must make this paradigm shift. Top Data Science Skills You Should Learn SL. No Top Data Science Skills to Learn 1 Data Analysis Online Certification Inferential Statistics Online Certification 2 Hypothesis Testing Online Certification Logistic Regression Online Certification 3 Linear Regression Certification Linear Algebra for Analysis Online Certification upGrad’s Exclusive Data Science Webinar for you – Watch our Webinar on The Future of Consumer Data in an Open Data Economy document.createElement('video'); https://cdn.upgrad.com/blog/sashi-edupuganti.mp4 Read our popular Data Science Articles Data Science Career Path: A Comprehensive Career Guide Data Science Career Growth: The Future of Work is here Why is Data Science Important? 8 Ways Data Science Brings Value to the Business Relevance of Data Science for Managers The Ultimate Data Science Cheat Sheet Every Data Scientists Should Have Top 6 Reasons Why You Should Become a Data Scientist A Day in the Life of Data Scientist: What do they do? Myth Busted: Data Science doesn’t need Coding Business Intelligence vs Data Science: What are the differences? Our learners also read: Free Python Course with Certification And lastly, the data scientist you’re looking for needs to have strong business acumen. Do they know your business? Do they know what problems you’re trying to solve? And do they find opportunities that you never would have guessed or spotted?
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by upGrad

14 May'16
UpGrad partners with Analytics Vidhya

5.67K+

UpGrad partners with Analytics Vidhya

We are happy to announce our partnership with Analytics Vidhya, a pioneer in the Data Science community. Analytics Vidhya is well known for its impressive knowledge base, be it the hackathons they organize or tools and frameworks that they help demystify. In their own words, “Analytics Vidhya is a passionate community for Analytics/Data Science professionals, and aims at bringing together influencers and learners to augment knowledge”. Explore our Popular Data Science Degrees Executive Post Graduate Programme in Data Science from IIITB Professional Certificate Program in Data Science for Business Decision Making Master of Science in Data Science from University of Arizona Advanced Certificate Programme in Data Science from IIITB Professional Certificate Program in Data Science and Business Analytics from University of Maryland Data Science Degrees We are joining hands to provide candidates of our PG Diploma in Data Analytics, an added exposure to UpGrad Industry Projects. While the program already covers multiple case studies and projects in the core curriculum, these projects with Analytics Vidhya will be optional for students to help them further hone their skills on data-driven problem-solving techniques. To further facilitate the learning, Analytics Vidhya will also be providing mentoring sessions to help our students with the approach to these projects. Our learners also read: Free Online Python Course for Beginners Top Essential Data Science Skills to Learn SL. No Top Data Science Skills to Learn 1 Data Analysis Certifications Inferential Statistics Certifications 2 Hypothesis Testing Certifications Logistic Regression Certifications 3 Linear Regression Certifications Linear Algebra for Analysis Certifications This collaboration brings great value to the program by allowing our students to add another dimension to their resume which goes beyond the capstone projects and case studies that are already a part of the program. Read our popular Data Science Articles Data Science Career Path: A Comprehensive Career Guide Data Science Career Growth: The Future of Work is here Why is Data Science Important? 8 Ways Data Science Brings Value to the Business Relevance of Data Science for Managers The Ultimate Data Science Cheat Sheet Every Data Scientists Should Have Top 6 Reasons Why You Should Become a Data Scientist A Day in the Life of Data Scientist: What do they do? Myth Busted: Data Science doesn’t need Coding Business Intelligence vs Data Science: What are the differences? Through this, we hope our students would be equipped to showcase their ability to dissect any problem statement and interpret what the model results mean for business decision making. This also helps us to differentiate UpGrad-IIITB students in the eyes of the recruiters. upGrad’s Exclusive Data Science Webinar for you – Transformation & Opportunities in Analytics & Insights document.createElement('video'); https://cdn.upgrad.com/blog/jai-kapoor.mp4 Check out our data science training to upskill yourself
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by Omkar Pradhan

09 Oct'16
Data Analytics Student Speak: Story of Thulasiram

5.68K+

Data Analytics Student Speak: Story of Thulasiram

When Thulasiram enrolled in the UpGrad Data Analytics program, in its first cohort, he was not very different for us, from the rest of our students in this. While we still do not and should not treat learners differently, being in the business of education – we definitely see this particular student in a different light. His sheer resilience and passion for learning shaped his success story at UpGrad. Humble beginnings Born in the small town of Chittoor, Andhra Pradesh, Thulasiram does not remember much of his childhood given that he enlisted in the Navy at a very young age of about 15 years. Right out of 10th standard, he trained for four years, acquiring a diploma in mechanical engineering. Thulasiram came from humble means. His father was the manager of a small general store and his mother a housewife. It’s difficult to dream big when leading a sheltered life with not many avenues for exposure to unconventional and exciting opportunities. But you can’t take learning out of the learner. “One thing I remember about school is our Math teacher,” reminisces Thulasiram, “He used to give us lot of puzzles to solve. I still remember one puzzle. If you take a chessboard and assume that all pawns are queens; you have to arrange them in such a way that none of the eight pawns should die. Every queen, should not affect another queen. It was a challenging task, but ultimately we did it, we solved it.” Navy & MBA At 35 years of age, Thulasiram has been in the navy for 19 years. Presently, he is an instructor at the Naval Institute of Aeronautical Technology. “I am from the navy and a lot of people don’t know that there is an aviation wing too. So, it’s like a dream; when you are a small child, you never dream of touching an aircraft, let alone maintaining it. I am very proud of doing this,” says Thulasiram on taking the initiative to upskill himself and becoming a naval-aeronautics instructor. When the system doesn’t push you, you have to take the initiative yourself. Thulasiram imbibed this attitude. He went on to enroll in an MBA program and believes that the program drastically helped improve his communication skills and plan his work better. How Can You Transition to Data Analytics? Data Analytics Like most of us, Thulasiram began hearing about the hugely popular and rapidly growing domain of data analytics all around him. Already equipped with the DNA of an avid learner and keen to pick up yet another skill, Thulasiram began researching the subject. He soon realised that this was going to be a task more rigorous and challenging than any he had faced so far. It seemed you had to be a computer God, equipped with analytical, mathematical, statistical and programming skills as prerequisites – a list that could deter even the most motivated individuals. This is where Thulsiram’s determination set him apart from most others. Despite his friends, colleagues and others that he ran the idea by, expressing apprehension and deterring him from undertaking such a program purely with his interests in mind – time was taken, difficulty level, etc. – Thulasiram, true to the spirit, decided to pursue it anyway. Referring to the crucial moment when he made the decision, he says, If it is easy, everybody will do it. So, there is no fun in doing something which everybody can do. I thought, let’s go for it. Let me push myself — challenge myself. Maybe, it will be a good challenge. Let’s go ahead and see whether I will be able to do it or not. UpGrad Having made up his mind, Thulasiram got straight down to work. After some online research, he decided that UpGrad’s Data Analytics program, offered in collaboration with IIIT-Bangalore that awarded a PG Diploma on successful completion, was the way to go. The experience, he says, has been nothing short of phenomenal. It is thrilling to pick up complex concepts like machine learning, programming, or statistics within a matter of three to four months – a feat he deems nearly impossible had the source or provider been one other than UpGrad. Our learners also read: Top Python Free Courses Favorite Elements Ask him what are the top two attractions for him in this program and, surprising us, he says deadlines! Deadlines and assignments. He feels that deadlines add the right amount of pressure he needs to push himself forward and manage time well. As far as assignments are concerned, Thulasiram’s views resonate with our own – that real-life case studies and application-based learning goes a long way. Working on such cases and seeing results is far superior to only theoretical learning. He adds, “flexibility is required because mostly only working professionals will be opting for this course. You can’t say that today you are free, because tomorrow some project may be landing in your hands. So, if there is no flexibility, it will be very difficult. With flexibility, we can plan things and maybe accordingly adjust work and family and studies,” giving the UpGrad mode of learning, yet another thumbs-up. Amongst many other great things he had to say, Thulasiram was surprised at the number of live sessions conducted with industry professionals/mentors every week. Along with the rest of his class, he particularly liked the one conducted by Mr. Anand from Gramener. Top Data Science Skills to Learn to upskill SL. No Top Data Science Skills to Learn 1 Data Analysis Online Courses Inferential Statistics Online Courses 2 Hypothesis Testing Online Courses Logistic Regression Online Courses 3 Linear Regression Courses Linear Algebra for Analysis Online Courses What Kind of Salaries do Data Scientists and Analysts Demand? Get data science certification from the World’s top Universities. Learn Executive PG Programs, Advanced Certificate Programs, or Masters Programs to fast-track your career. Read our popular Data Science Articles Data Science Career Path: A Comprehensive Career Guide Data Science Career Growth: The Future of Work is here Why is Data Science Important? 8 Ways Data Science Brings Value to the Business Relevance of Data Science for Managers The Ultimate Data Science Cheat Sheet Every Data Scientists Should Have Top 6 Reasons Why You Should Become a Data Scientist A Day in the Life of Data Scientist: What do they do? Myth Busted: Data Science doesn’t need Coding Business Intelligence vs Data Science: What are the differences? upGrad’s Exclusive Data Science Webinar for you – ODE Thought Leadership Presentation document.createElement('video'); https://cdn.upgrad.com/blog/ppt-by-ode-infinity.mp4 Explore our Popular Data Science Courses Executive Post Graduate Programme in Data Science from IIITB Professional Certificate Program in Data Science for Business Decision Making Master of Science in Data Science from University of Arizona Advanced Certificate Programme in Data Science from IIITB Professional Certificate Program in Data Science and Business Analytics from University of Maryland Data Science Courses “Have learned most here, only want to learn..” Interested only in learning, Thulasiram made this observation about the program – compared to his MBA or any other stage of life. He signs off calling it a game-changer and giving a strong recommendation to UpGrad’s Data Analytics program. We are truly grateful to Thulasiram and our entire student community who give us the zeal to move forward every day, with testimonials like these, and make the learning experience more authentic, engaging, and truly rewarding for each one of them. If you are curious to learn about data analytics, data science, check out IIIT-B & upGrad’s PG Diploma in Data Science which is created for working professionals and offers 10+ case studies & projects, practical hands-on workshops, mentorship with industry experts, 1-on-1 with industry mentors, 400+ hours of learning and job assistance with top firms.
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by Apoorva Shankar

07 Dec'16
Decoding Easy vs. Not-So-Easy Data Analytics

5.12K+

Decoding Easy vs. Not-So-Easy Data Analytics

Authored by Professor S. Sadagopan, Director – IIIT Bangalore. Prof. Sadagopan is one of the most experienced academicians on the expert panel of UpGrad & IIIT-B PG Diploma Program in Data Analytics. As a budding analytics professional confounded by jargon, hype and overwhelming marketing messages that talk of millions of upcoming jobs that are paid in millions of Rupees, you ought to get clarity about the “real” value of a data analytics education. Here are some tidbits – that should hopefully help in reducing your confusion. Some smart people can use “analytical thinking” to come up with “amazing numbers”; they are very useful but being “intuitive”, they cannot be “taught.” For example: Easy Analytics Pre-configuring ATMs with Data Insights  “We have the fastest ATM on this planet” Claimed a respected Bank. Did they get a new ATM made especially for them? No way. Some smart employee with an analytical mindset found that 90% of the time that users go to an ATM to withdraw cash, they use a fixed amount, say Rs 5,000. So, the Bank re-configured the standard screen options – Balance Inquiry, Withdrawal, Print Statement etc. – to include another option. Withdraw XYZ amount, based on individual customer’s past actions. This ended up saving one step of ATM operation. Instead of selecting the withdrawal option and then entering the amount to be withdrawn, you could now save some time – making the process more convenient and intuitive. A smart move indeed, however, this is something known as “Easy Analytics” that others can also copy. In fact, others DID copy, within three months! A Start-Up’s Guide to Data Analytics Hidden Data in the Weather In the sample data-sets that used to accompany a spreadsheet product in the 90’s, there used to be data on the area and population of every State in the United States. There was also an exercise to teach the formula part of the spreadsheet to compute the population density (population per sq. km). New Jersey, with a population of 467 per sq. km, is the State with the highest density. While teaching a class of MBA students in New Jersey, I met an Indian student who figured out that in terms of population density, New Jersey is more crowded than India with 446 people per sq. km!  An interesting observation, although comparing a State with a Country is a bit misleading. Once again, an Easy Analytics exercise leading to a “nice” observation! Some simple data analytics exercises can be routinely done, and are made relatively easier, thanks to amazing tools: B-School Buying Behavior Decoded In a B-School in India that has a store on campus, (campus is located far from the city center) some smart students put several years of sales data of their campus store. They were excited by the phenomenal computer power and near, idiot-proof analytics software. The real surprise, however, was that eight items accounted for 85% of their annual sales. More importantly, these eight items were consumed in just six days of the year! Everyone knew that a handful of items were the only fast-moving items, but they did not know the extent (85%) or the intensity (consumption in just six days) of this. It turns out that in the first 3 days of the semester the students would stock the items for the full semester! The B-School found it sensible to request a nearby store to prop up a temporary stall for just two weeks at the beginning of the semesters and close down the Campus Store. This saved useful space and costs without causing major inconvenience to the students. A good example of Easy Analytics done with the help of a powerful tool. Top 4 Data Analytics Skills You Need to Become an Expert! The “Not So Easy” Analytics needs deep analytical understanding, tools, an ‘analytical mindset’ and some hard work. Here are two examples, one taken from way back in the 70’s and the other occurring very recently: Not-So-Easy Analytics To Fly or Not to Fly, That is the Question Long ago, the American Airlines perfected planned overbooking of airline seats, thanks to SABRE Airline Reservation system that managed every airline seat. Armed with detailed past data of ‘empty seats’ and ‘no show’ in every segment of every flight for every day through the year, and modeling airline seats as perishable commodities, the American Airlines was able to improve yield, i.e., utilization of airplane capacity. They did this through planned overbooking – selling more tickets than the number of seats, based on projected cancellations. Explore our Popular Data Science Online Certifications Executive Post Graduate Programme in Data Science from IIITB Professional Certificate Program in Data Science for Business Decision Making Master of Science in Data Science from University of Arizona Advanced Certificate Programme in Data Science from IIITB Professional Certificate Program in Data Science and Business Analytics from University of Maryland Data Science Online Certifications If indeed more passengers showed up than the actual number of seats, American Airlines would request anyone volunteering to forego travel in the specific flight, with the offer to fly them by the next flight (often free) and taking care of hotel accommodation if needed. Sometimes, they would even offer cash incentives to the volunteer to opt-out. Using sophisticated Statistical and Operational Research modeling, American Airlines would ensure that the flights went full and the actual incidents of more passengers than the full capacity, was near zero. In fact, many students would look forward to such incidents so that they could get incentives, (in fact, I would have to include myself in this list) but rarely were they rewarded!) upGrad’s Exclusive Data Science Webinar for you – Transformation & Opportunities in Analytics & Insights document.createElement('video'); https://cdn.upgrad.com/blog/jai-kapoor.mp4 What American Airlines started as an experiment has become the standard industry practice over the years. Until recently, a team of well-trained (often Ph.D. degree holders) analysts armed with access to enormous computing power, was needed for such an analytics exercise to be sustained. Now, new generation software such as the R Programming language and powerful desktop computers with significant visualization/graphics power is changing the world of data analytics really fast. Anyone who is well-trained (not necessarily requiring a Ph.D. anymore) can become a first-rate analytics professional. Top Data Science Skills You Should Learn SL. No Top Data Science Skills to Learn 1 Data Analysis Online Certification Inferential Statistics Online Certification 2 Hypothesis Testing Online Certification Logistic Regression Online Certification 3 Linear Regression Certification Linear Algebra for Analysis Online Certification Unleashing the Power of Data Analytics Our learners also read: Free Python Course with Certification Read our popular Data Science Articles Data Science Career Path: A Comprehensive Career Guide Data Science Career Growth: The Future of Work is here Why is Data Science Important? 8 Ways Data Science Brings Value to the Business Relevance of Data Science for Managers The Ultimate Data Science Cheat Sheet Every Data Scientists Should Have Top 6 Reasons Why You Should Become a Data Scientist A Day in the Life of Data Scientist: What do they do? Myth Busted: Data Science doesn’t need Coding Business Intelligence vs Data Science: What are the differences?   Cab Out of the Bag Uber is yet another example displaying how the power of data analytics can disrupt a well-established industry. Taxi-for-sure in Bangalore and Ola Cabs are similar to Uber. Together, these Taxi-App companies (using a Mobile App to hail a taxi, the status monitor the taxi, use and pay for the taxi) are trying to convince the world to move from car ownership to on-demand car usage. A simple but deep analytics exercise in the year 2008 gave such confidence to Uber that it began talking of reducing car sales by 25% by the year 2025! After building the Uber App for iPhone, the Uber founder enrolled few hundreds of taxi customers in San Francisco and few hundreds of taxi drivers in that area as well. All that the enrolled drivers had to do was to touch the Uber App whenever they were ready for a customer. Similarly, the enrolled taxi customers were requested to touch the Uber App whenever they were looking for a taxi. Thanks to the internet-connected phone (connectivity), Mobile App (user interface), GPS (taxi and end-user location) and GIS (location details), Uber could try connecting the taxi drivers and the taxi users. The real insight was that nearly 90% of the time, taxi drivers found a customer, less than 100 meters away! In the same way, nearly 90% of the time, taxi users were connected with their potential drivers in no time, not too far away. Unfortunately, till the Uber App came into existence, riders and taxi drivers had no way of knowing this information. More importantly, they both had no way of reaching each other! Once they had this information and access, a new way of taxi-hailing could be established. With back-end software to schedule taxis, payment gateway and a mobile payment mechanism, a far more superior taxi service could be established. Of course, near home, we had even better options like Taxi-for-sure trying to extend this experience even to auto rickshaws. The rest, as they say, is “history in the making!” Deep dive courses in data analytics will help prepare you for such high impact applications. It is not easy, but do remember former US President Kennedy’s words “we chose to go to the Moon not because it is easy, but because it is hard!” Get data science certification from the World’s top Universities. Learn Executive PG Programs, Advanced Certificate Programs, or Masters Programs to fast-track your career.  
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by Prof. S. Sadagopan

14 Dec'16
Launching UpGrad’s Data Analytics Roadshow – Are You Game?

5.14K+

Launching UpGrad’s Data Analytics Roadshow – Are You Game?

We, at UpGrad, are excited to announce a brand new partnership with various thought leaders in the Data Analytics industry – IIIT Bangalore, Genpact, Analytics Vidhya and Gramener – to bring to you a one-of-a-kind Analytics Roadshow! As part of this roadshow, we will be conducting several back-to-back events that focus on different aspects of analytics, creating interaction points across India, to do our bit for a future ready and analytical, young workforce.  Also Read: Analytics Vidhya article on the UpGrad Data Analytics Roadshow Here is the line-up for the roadshow, to give you a better sense of what to expect: 9 webinars – These webinars (remote) will be conducted by industry experts and are aimed at increasing analytics awareness, providing a way for aspirants to interact with industry practitioners and getting their tough questions answered. 11 workshops – The workshops will be in-person events to take these interactions to the next level. These would be spread across 6 cities – Delhi, Bengaluru, Hyderabad, Chennai, Mumbai and Pune. So, if you are in any of these cities, we are looking forward to interact with you. Featured Data Science program for you: Master of Science in Data Science from from IIIT-B 2 Conclaves – These conclaves are larger events with a pre-defined agendas and time for networking. The first conclave is happening on the 17th of December in Bengaluru.  Explore our Popular Data Science Online Certifications Executive Post Graduate Programme in Data Science from IIITB Professional Certificate Program in Data Science for Business Decision Making Master of Science in Data Science from University of Arizona Advanced Certificate Programme in Data Science from IIITB Professional Certificate Program in Data Science and Business Analytics from University of Maryland Data Science Online Certifications Hackathon – Time to pull up your sleeves and showcase your nifty skills. We will be announcing the format of the event shortly. “We find that the IT in­dustry is ab­sorb­ing al­most half of all of the ana­lyt­ics jobs. Banking is the second largest, but trails at al­most one fourth of IT’s re­cruit­ing volume. It is in­ter­est­ing that data rich in­dus­tries like Retail, Energy and Insurance are trail­ing near the bot­tom, lower than even con­struc­tion or me­dia, who handle less data. Perhaps these are ripe for dis­rup­tion through ana­lyt­ics?” Our learners also read: Learn Python Online for Free Mr. S. Anand, CEO of Gramener, wonders aloud. Read our popular Data Science Articles Data Science Career Path: A Comprehensive Career Guide Data Science Career Growth: The Future of Work is here Why is Data Science Important? 8 Ways Data Science Brings Value to the Business Relevance of Data Science for Managers The Ultimate Data Science Cheat Sheet Every Data Scientists Should Have Top 6 Reasons Why You Should Become a Data Scientist A Day in the Life of Data Scientist: What do they do? Myth Busted: Data Science doesn’t need Coding Business Intelligence vs Data Science: What are the differences? upGrad’s Exclusive Data Science Webinar for you – Watch our Webinar on The Future of Consumer Data in an Open Data Economy document.createElement('video'); https://cdn.upgrad.com/blog/sashi-edupuganti.mp4   Top Data Science Skills You Should Learn SL. No Top Data Science Skills to Learn 1 Data Analysis Online Certification Inferential Statistics Online Certification 2 Hypothesis Testing Online Certification Logistic Regression Online Certification 3 Linear Regression Certification Linear Algebra for Analysis Online Certification Get data science certification from the World’s top Universities. Learn Executive PG Programs, Advanced Certificate Programs, or Masters Programs to fast-track your career.
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by Apoorva Shankar

15 Dec'16
What’s Cooking in Data Analytics? Team Data at UpGrad Speaks Up!

5.22K+

What’s Cooking in Data Analytics? Team Data at UpGrad Speaks Up!

Team Data Analytics is creating the most immersive learning experience for working professionals at UpGrad. Data Insider recently checked in to me to get my insights on the data analytics industry; including trends to watch out for and must-have skill sets for today’s developers. Here’s how it went: How competitive is the data analytics industry today? What is the demand for these types of professionals? Let’s talk some numbers, a widely-quoted McKinsey report states that the United States will face an acute shortage of around 1.5 million data professionals by 2018. In India, which is emerging as the global analytics hub, the shortage of such professionals could go up to as high as 200,000. In India alone, the number of analytics jobs saw a 120 percent rise from June 2015 to June 2016. So, we clearly have a challenge set out for us. Naturally, because of acute talent shortage, talented professionals are high in demand. Decoding Easy vs. Not-So-Easy Analytics What trends are you following in the data analytics industry today? Why are you interested in them? There are three key trends that we should watch out for: Personalization I think the usage of data to create personalized systems is a key trend being adopted extremely fast, across the board. Most of the internet services are removing the anonymity of online users and moving towards differentiated treatment. For example, words recommendations when you are typing your messages or destinations recommendations when you are using Uber. Our learners also read: Learn Python Online for Free End of Moore’s Law Another interesting trend to watch out for is how companies are getting more and more creative as we reach the end of Moore’s Law. Moore’s Law essentially states that every two years we will be able to fit double the number of transistors that could be fit on a chip, two years ago. Because of this law, we have unleashed the power of storing and processing huge amounts of data, responsible for the entire data revolution. But what will happen next? IoT Another trend to watch out for, for the sheer possibilities it brings. It’s the emergence of smart systems which is made possible by the coming together of cloud, big data, and IoT (internet of things). Explore our Popular Data Science Courses Executive Post Graduate Programme in Data Science from IIITB Professional Certificate Program in Data Science for Business Decision Making Master of Science in Data Science from University of Arizona Advanced Certificate Programme in Data Science from IIITB Professional Certificate Program in Data Science and Business Analytics from University of Maryland Data Science Courses What skill sets are critical for data engineers today? What do they need to know to stay competitive? A good data scientist sits at a rare overlap of three areas: Domain Knowledge This helps understand and appreciate the nuances of a business problem. For e.g, an e-commerce company would want to recommend complementary products to its buyers. Statistical Knowledge Statistical and mathematical knowledge help to inform data-driven decision making. For instance, one can use market basket analysis to come up with complementary products for a particular buy. Technical Knowledge This helps perform complex analysis at scale; such as creating a recommendation system that shows that a buyer might prefer to also buy a pen while buying a notebook. How Can You Transition to Data Analytics? Outside of their technical expertise, what other skills should those in data analytics and business intelligence be sure to develop? Ultimately, data scientists are problem solvers. And every problem has a specific context, content and story behind it. This is where it becomes extremely important to tie all these factors together – into a common narrative. Essentially all data professionals need to be great storytellers. In this respect, one of the key skills for analysts to sharpen would be, breaking down the complexities of analytics for others working with them. They can appreciate the actual insights derived – and work toward a common business goal. In addition, what is as crucial is getting into a habit of constantly learning. Even if it means waking up every morning and reading what’s relevant and current in your domain. Top Essential Data Science Skills to Learn SL. No Top Data Science Skills to Learn 1 Data Analysis Certifications Inferential Statistics Certifications 2 Hypothesis Testing Certifications Logistic Regression Certifications 3 Linear Regression Certifications Linear Algebra for Analysis Certifications What should these professionals be doing to stay ahead of trends and innovations in the field? Professionals these days need to continuously upskill themselves and be willing to unlearn and relearn. The world of work and the industrial landscape of technology-heavy fields such as data analytics is changing every year. The only way to stay ahead, or even at par with these trends, is to invest in learning, taking up exciting industry-relevant projects, participating in competitions like Kaggle, etc. How important is mentorship in the data industry? Who can professionals look toward to help further their careers and their skills? Extremely important. Considering how fast this domain has emerged, academia and universities, in general, have not had the chance to keep up equally fast. Hence, the only way to stay industry-relevant with respect to this domain is to have industry-specific learning. This can only be done in two ways – through real-life case studies and mentors who are working/senior professionals and hail from the data analytics industry. In fact, at UpGrad, there is a lot of stress on industry mentorship for aspiring data specialists. This is in addition to a whole host of case studies and industry-relevant projects. Get data science certification from the World’s top Universities. Learn Executive PG Programs, Advanced Certificate Programs, or Masters Programs to fast-track your career. Read our popular Data Science Articles Data Science Career Path: A Comprehensive Career Guide Data Science Career Growth: The Future of Work is here Why is Data Science Important? 8 Ways Data Science Brings Value to the Business Relevance of Data Science for Managers The Ultimate Data Science Cheat Sheet Every Data Scientists Should Have Top 6 Reasons Why You Should Become a Data Scientist A Day in the Life of Data Scientist: What do they do? Myth Busted: Data Science doesn’t need Coding Business Intelligence vs Data Science: What are the differences?   Where are the best places for data professionals to find mentors? upGrad’s Exclusive Data Science Webinar for you – Transformation & Opportunities in Analytics & Insights document.createElement('video'); https://cdn.upgrad.com/blog/jai-kapoor.mp4 While it’s important for budding or aspiring data professionals to tap into their networks to find the right mentors, it is admittedly tough to do so. There are two main reasons that can be blamed for this. First, due to the nascent stage, the industry is at, it is extremely difficult to find someone with the requisite skill sets to be a mentor. Even if you find someone with considerable experience in the field, not everybody has the time and inclination to be an effective mentor. Hence most people don’t know where to go to be mentored. That’s where platforms like UpGrad come in, which provide you with a rich, industry-relevant learning experience. Nowhere else are you likely to chance upon such a wide range of industry tie-ups or associations for mentorship from very senior and reputed professionals. How Can You Transition to Data Analytics? What resources should those in the data analytics industry be using to ensure they’re educated and up-to-date on developments, trends, and skills? There are many. For starters, here are some good and pretty interesting blogs and resources that would serve aspiring/current data analysts well to keep up with Podcasts like Data Skeptic, Freakonomics, Talking Machines, and much more.   This interview was originally published on Data Insider.  
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by Rohit Sharma

23 Dec'16