Why study Data Science?
Tags: datascience, datascientist, dataanalytics
Published: 2022-01-27 06:10:26

There has been a revolutionary change in the behavioral pattern of customers in the case of online purchases, stock market investment, advertising products to other customers, and so on. Each of these activities requires an in-depth analysis of existing relevant data which makes Data Science a promising field of study in today’s fast-growing data-driven world.

A few of the industry verticals where data science has found its prominence and is used for operational and strategic decision making are discussed below:

**Ecommerce:** Ecommerce sites hugely involve data science for maximizing revenue and profitability. These sites analyze the shopping and purchasing behavior of customers and accordingly recommend products to customers for more purchases online.

**Finance:** The finance market is an emerging field in the data industry. The financial analytics market takes care of risk analysis, fraud detection, shareholders’ upcoming share status, working capital management, and so on.

**Retail:** Retail industries take care of a 360-degree view and feedback reviews of customers. The retail analytics market analyzes customers’ purchasing trends and demands in order to get products based on customers’ liking. Retail industries involve data science for optimal pricing, personalized offers, better marketing strategies, market basket analysis, stock management, and so on.

**Healthcare:** The healthcare sector also nowadays heavily relies on analytics of patient data to predict diseases and health issues. Healthcare industries make an analysis of data-driven patient quality care, improved patient care, classification of the type of symptoms of patients and predicted health deficiencies, and so on.

**Education:** The sources of data in education is vast, starting from student-centric data, enrollment in various courses, scholarship and fee details, examination results, and so on. Education analytics play a major role in academic institutions for better admission scenarios, empowerment of students for successful examination results, and all-around student performance.

**Human Resource (HR):** HR analytics involves HR-related data that can be used for building strong leadership, employee acquisition, employee retention, workforce optimization, and performance management.

**Sports:** Nowadays, sports analytics is often used in international tournaments to analyze the performance of players, the predicted scores, prevention of injuries, and the possibility of winning or losing a match by a particular team.

The use of data science is nowadays found in every prominent domain, a few of which have been addressed above. The few other sectors that need a mention are telecom industries, sales, supply chain management, risk monitoring, manufacturing industries, and IT companies. The recent competitions in businesses and companies consider data science no longer as an optional requirement but rather hire data analysts and data scientists for the same to deal with hidden massive data to provide meaningful results and generate reports to arrive at profit-making decisions. Also, the recent trends in the job market show that data analysts, data scientists, and data engineers have a huge demand in the IT companies and this demand will continue for the next decade. Hence, becoming a data analyst, data scientist, or data engineer can uplift your job profile and the demand will be witnessed in many companies in the years to come.

Hope this was helpful.