Page 6 - Konect Science & Technology Magazine Cover

Why is Data Analytics a crucial

skill for an MBA student?

Organizations today spend millions of dollars to organize their data W R I T T E N B Y - S O H A M N A Y A K
to gather actionable insights and eventually monetize them.
However, there is a knowledge transfer gap in traditional B-Schools
to understand data and turn them into information that could be Product/Tech firms and the IT arms of big conglomerates use analytics in
used in day-to-day affairs.. : a big way to drive their business decisions. Product Analyst roles in
prominent tech startups require knowledge of making effective
From a business perspective, in addition to finance, marketing and dashboards and visualizations to measure the product's key performance
strategy aspects, employees should have a comprehensive overview metrics apart from competitive and market strategies. These
36
of the vast amount of data flowing through the organization. organizations' business roles involve regular interaction with the analytics
and engineering team to understand different business scenarios. With a
good conceptual knowledge of some statistical methods and visualization
basics, the transition to an organization in analytics management and
consulting practice would be more effortless..

During MBA studies, the core courses to focus on for a career in the
analytics management space is:

‣ Statistical and Quantitative techniques (Ex: Hypothesis Test, Regression)
‣ Information Systems (Ex: Data mining)
‣ Operations Research (Ex: Optimization Problems)
‣ Visualization Software (Ex: Tableau, Power BI)
‣ Software Language (Basics of SQL, R)

Software knowledge is not a mandatory requirement by companies.
However, fundamental knowledge in the above areas dramatically
increases the opportunities and job prospects available to an MBA
graduate in Data Consulting, Product Analytics, Business/Data Analyst,
etc.
Traditional Operations roles in different FMCGs use extensive analytics
applications to optimize inventory, measure asset utilization & shelf
availability. It also helps in forecasting the demand of products, staffing
requirements, and minimizing stock-outs. The application of supply chain
analytics is used for route optimization and reverse logistics diagnosis.

Customer experience is an important area where firms are looking to
Core analytics value proposition in companies having large delight the customer at every step of their interaction. Analytics is used to
amounts of data: increase customer engagement while reducing bad experiences.
Customer gratification, product recommendations, and targeted
Descriptive analysis: Understanding the historical data to promotions are all widely used insights that can be captured through the
understand changes that occurred in the business. Example: Year on system's voluminous amount of data.
Year / Month on Month Comparison of Sales data in an Automobile
Manufacturer. Apart from corporates, even companies in the social impact sector,
48
NGOs, and the CSR wings of corporates have utilized data analytics to
Predictive analysis: Predicting future performance based on past answer pertinent questions. For example correlation of a dip in school
data of an organization. Example: Predicting customer churn rate for attendance in rural schools with deteriorating water quality that affects
an e-commerce platform. students' health could be answered by analyzing vast amounts of open
data sources.
Prescriptive analysis: Optimization strategy formulation to enhance
business performance by analyzing raw data. Example: Pricing of Organizations nowadays are also looking to hire well-rounded individuals
airline tickets based on various factors of demand, fuel prices, weather, who would effectively understand data and guide different teams on
etc. specific business requirements to increase the firm's overall productivity.

DARVIX CONNECT | 5 darvix email