COURSE DESCRIPTION
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 WalMart, Google, Capital One, and Disney. For example, Capital One
uses sophisticated analytic capabilities to match credit card offerings to customers more accurately
than their competition. WalMart uses analytics to monitor and update its inventory in a way that
allows it to serve its customers at an exceptionally low cost. In addition, many current and recent
startups such as Palantir and Splunk are based on the application of analytics to large data bases.
With the increasing availability of broad and deep sources of information — so-called “Big Data”
— business analytics are becoming an even more critical capability for enterprises of all types and
all sizes.
In this course, you will learn to identify, evaluate, and capture business analytic opportunities that
create value. Toward this end, you will learn basic analytic methods and analyze case studies on
organizations that successfully deployed these techniques. In the first part of the course, we focus
on how to use data to develop insights and predictive capabilities using machine learning, data
mining and forecasting techniques. In the second part, we focus on the use of optimization to
support decision-making in the presence of a large number of alternatives and business constraints.
Finally, throughout the course, we explore the challenges that can arise in implementing analytical
approaches within an organization.
Learning Outcome.
1. Identify, evaluate, and capture business analytic opportunities that create value.
2. Understand basic analytic methods and analyze case studies on organizations that successfully deployed these techniques
3. Using data to develop insights and predictive capabilities using machine learning, data mining and forecasting techniques.
4. Application of optimization to support decision-making in the presence of a large number of alternatives and business constraints.
5. Explore the challenges that can arise in implementing analytical approaches within an organization
Employment Objectives.
1. Ability to think critically about data and the analyses based on those data — whether conducted by you or someone else.
2. Ability to identify opportunities for creating value using business analytics.
3. Ability to estimate the value created using business analytics to address an opportunity.
4. Ability to understand and apply these methods to drive value.