DSS & Warehousing Systems Chapter 14 Efrem Mallach Prepared by Luvai Motiwalla Irwin/McGraw-Hill Copyright © 2000 by The McGraw-Hill Companies, Inc. All rights reserved.

Analyzing the Contents of the Data Warehouse Active analysis: user queries OLAP OLAP software architecture Web – based OLAP General OLAP product characteristics Automated analysis: data mining Creating a decision tree Neural networks Nearest neighbor approaches Putting the results to use

Active Analysis : User Queries Many decisions can be made well on the basis of a series of questions and answers.

OLAP Online analytical processing(OLAP) – is the mode of operation where the user chooses to go deeper into detail (drilling down) until the necessary decisions have been made.

OLAP Software Architecture Most OLAP software whichever approach it follows, is designed to work in client/server mode.

Web – Based OLAP These products allow users of web browsers or network computers to access and analyze data warehouse data.

General OLAP Product Characteristics There are many OLAP products on the market but fortunately for the Prospective OLAP software buyers they all share some common characteristics.

Automated Analysis : Data Mining In data mining , the user specifies what he or she wants to find out and on what he or she wants the answer to depend. Advantages and disadvantages of data mining

Creating a Decision Tree How is a decision tree created? Correlation and other statistical analysis

Neural Networks A neural network tries to mimic the way human and animal brains functions

Nearest Neighbor Approaches This approach involves finding old cases that are close to each new one and assuming its outcome will match the majority of those neighbors.

Putting the Results to Use A good data mining project will divide the business entities in the data warehouse database into sections that vary significantly along a dimension of value to the organization.