Business analytics refers to the ways in which enterprises such as businesses, non-profits, and governments can use data to gain insights and make better decisions. Business analytics is applied in operations, marketing, finance, and strategic planning among other functions. The ability to use data effectively to drive rapid, precise and profitable decisions has been a critical strategic advantage for companies as diverse as Wal-Mart, Google, Capital One and Disney.

Many organizations have a wealth of data residing in their databases, and generate additional valuable data that is often not captured. With the proliferation of data repositories in enterprises and organizations and the acceleration of computing power, there is an increasing demand for making sense of the archived data. Business Analytics has emerged as one of the most powerful techniques to achieve the above goal. This course aims to provide students with a broad background on business analytics concepts and techniques, exposure to business intelligence tools, application of business analytical techniques to improve marketing, sales, and customer relationship management. Given the close connection of Business Analytics to real world application and its potential in improving the performance of business operations, data mining techniques, business intelligence, and business analytics will be discussed in various business and organizational contexts.

The course emphasizes that business analytics is not a theoretical discipline: these techniques are only interesting and important to the extent that they can be used to provide real insights and improve the speed, reliability, and quality of decisions. The course discuss scenarios from a variety of business disciplines, including the use of business analytics to support customer relationship management (Analytical CRM) decisions, decisions in the entertainment industry, finance, and human relations.

Course Objective:

The three main objective of the course are to enable students to:

1. Approach business problems using data-analytical approach (Inter-Disciplinary & Cross Functional Approach) by identifying opportunities to derive Business value using business analytic techniques.

2. Interact competently on the topic of data-driven business intelligence. Know the basics of data mining techniques and how they can be applied to interact effectively with CTOs, expert data miners, and business analysts. This competence will allow the student to envision data science opportunities.

3. Acquire Hands-on Experience of Business Analytics Tools & Techniques Course.