Competing+on+Analytics+II

=Competing on analytics II= Tuesday, April 1

**Topic overview:**
As we saw from our previous discussion on //Competing on Analytics//, Davenport and Harris build a compelling case that organizations that have successfully developed the ability to capture, analyze, and act on data in innovative ways can use their analytic capabilities to powerful advantage.

In todays class we will build on the technical foundations discusssed in the previous two classes on data warehousing and explore, in much greater detail, what organizations need to do to build a data warehousing infrastructure that can support analytics=based competition. We will look at common business processes that organizations enhance with analytics and explore the data capture, cleansing, and storage requirements for supporting such a capability.

Specific topics that we will cover include:
 * Common business processes and decisions that organizations choose to use as a basis for analytics competition ([DH07] ch. 4 and 5).
 * Why these are good (or questionable) choices, and under what circumstances their use might be appropriate
 * The data that an organization needs to capture in order to be effective at competing with these processes
 * Techniques for selecting the data to capture and exploit in your data warehouse or data mart(s)
 * Issues in insuring that your data is a good foundation for decision making

Class materials:
Slides: In-class exercise:

**Preparation for class:**
Prior to class, you will need to have read chapters 4, 5, and 8 of Competing on Analytics [DH07]
 * [DH07] Davenport, Thomas H., and Harris, Jeanne G., Competing on Analytics – The New Science of Winning, Harvard Business School Press, Boston, MA, 2007. ISBN: 978-1-4221-0332-6 (course textbook)