For modern-day enterprises, Big Data has become the magic ingredient for the recipe of success. Big Data refers to the large data sets relating to human behaviour and interactions that can be processed or analyzed computationally to uncover noteworthy details. Business survival in the digital age means unlocking the powers of these gigabytes of data and gaining actionable insights.
Moreover, processing, combining, associating, and analyzing the available information can deliver enormous value, from supporting corporate actions to refining lower-level operations. Data science may be the buzzword across industries, but there is still some mystery around it. Let us understand what it entails and how it can transform businesses.
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What Data Scientists Do
Data Science is a field that borrows from Mathematics, Computer Science, and Statistics. It covers techniques like information management, data mining, visualization, etc. that help make sense of all the data that is incomprehensible in its raw form. Data scientists are specialists who work across departments to derive valuable information and further contribute to systematic decision-making.
Data scientists can also use big data methodologies to develop predictive fraud propensity models that help in mitigating risks and frauds. Such models can recognize unusual data and help ensure timely responses by creating alerts.
Another way in which data scientists contribute to organizational success is by matching the offerings to customer needs. Application of data science can help identify when and where the product or service is in high demand, and what is the profile of the current customers. It, thus, becomes easier to deliver relevant products and also make tweaks and updates in the existing strategies.
Further, sales and marketing teams can also benefit from understanding the audience better. They can create personalized customer experiences, which can improve customer satisfaction and lead to customer retention.
These are only a few of the many things that data scientists do in modern-day organizations. Now, let’s look at some of the advantages of integrating data science in business.
How Data Science Adds Value to the Business
1. Empowering Management
By measuring, tracking, and recording performance metrics and other useful information, data science enhances the analytical capacity of senior-level staff. Data science specialists convert raw data into processed information, analyze it and present the same to managerial staff. As a result, the management can not only dig deeper into critical organizational issues but also understand them from a well-rounded perspective.
2. Steering Actions Based on Trends
Data science can help predict and track upcoming trends to keep the business ahead of the curve. Directing the resources to the suggested proposition in time may generate long-term gains in terms of sustained competitive advantage and profitability.
3. Focusing on Core Issues
Having a data analytics system in place also requires that the staff is well-versed with it. A simple demonstration of the analytical product’s features and uses can help everyone understand their role in addressing key business challenges. Moreover, they devote their energies to core areas and work to strengthen the same and attain goals.
4. Identifying New Opportunities
Data science can improve existing processes and assumptions through new methods and algorithms. Data scientists interact with the current analytics system, question it, and suggest relevant updates. In this way, organizations become flexible and adaptable, deriving value from spotting opportunities as they arise. Read: Data Science Skills
5. Evidence-Based Decision Making
A business can eliminate its risk to a great extent through data science. Data can be gathered from multiple channels and analyzed to create models that simulate alternative actions. This exercise helps in finding out the best possible outcome and enables the business to make decisions backed by evidence. When operating in an uncertain environment, data-linked suggestions become a cushion for powering ahead.
6. Testing and Reviewing Steps
An organization has many cogs running at the same time. It is integral to monitor which initiatives are well-oiled and benefitting the organization, and which activities have failed to contribute anything valuable. Here, data science works its magic by measuring the key performance areas and quantifying their success. Conducting a review is also crucial in guiding future actions.
7. Knowing the Target Audience
Consumer data can be collected from a variety of sources. Organizations generally use Google analytics and customer surveys to gather data points on their target customers. But not all of these data points may be useful on their own. They may have to be combined with other data points to discover meaningful information. Data science facilitates this exercise and assists business teams in learning more about their target audience. Carrying out a comprehensive analysis supports precise target group identification and successful advertisement and promotion campaigns.
8. Recruiting the Right Talent
Nowadays, HR departments get teemed with resumes from social media, job portals, and corporate databases. And data science makes the recruiters’ job easy by processing the large volume of applications. Picking the right candidate for the job at hand is not a tedious task, but a sophisticated exercise for data scientists. They can mine vast amounts of data points, develop data-driven aptitude tests and games, and thereby assist accurate selection.
So, data science generates business value in a variety of ways. From hiring the right candidates to improving processes and refining decisions, it elevates the overall organizational performance. The data science tools, techniques, and methodologies connected to the field churn the ocean of raw data to extract useful knowledge for businesses. Therefore, it is no surprise that today data science is a growing field that has several applications across different industries!
If you are curious about learning data science to be in the front of fast-paced technological advancements, check out upGrad & IIIT-B’s PG Diploma in Data Science.
What are the applications of data science?
Data Science is governing a lot of technical domains as data has become a necessity. The following are the major applications of data science - The finance and banking sector is one of the earliest sectors which started using data science, as there is a dealing of a huge chunk of data on a regular basis. The healthcare sector uses data science predominantly in areas including Image diagnosis, research in medicine, and genetics. Other fields include airlines, transport, gaming, and manufacturing.
In what areas one must excel in to become a data scientist?
The following skills are necessary to be in your arsenal if you are a data science aspirant and want to crack good opportunities: Statistics and Probability are the two most important mathematical concepts of Data Science. Descriptive statistics including mean, median, and mode, linear regression, hypothesis testing constitutes the majority of the topics of statistics and probability. You must go with one programming language and master it to code in it. There are plenty of languages out there but Python is the most preferable language due to the libraries and modules it provides. Machine Learning and Deep Learning are two separate domains and the subsets of Data Science at the same time. These topics will help you to get far in data science. Data Visualization is the art of visualizing the data in the form of charts and graphs to make it more understandable and profitable. Data visualization is a prominent skill and is highly in demand.
Is there any future of data science?
Data Science is indeed trending the charts with our ever-increasing dependencies on data and technology. There is a huge gap between the demand and the supply of data scientists which makes it one of the highest paying fields of 2021. A data scientist with 5 years of experience earns around $300,000 per year. A decent data scientist earns around $123,000 per annum whereas the median salary of data scientists is around $91,000 per annum. This is just the base salary. Data scientists also get an attractive media bonus of around $8k within a range of $1K-$17k.