Data Analysis/OLAP

Data Analysis/OLAP is most fundamental way to make sense out of your data. It involves looking at the data from all possible angles, slicing & dicing on various dimensions, drilling up/down, applying filters, exception highlighting, graphs and other presentation tools, doing time trending analysis. Whether you are doing a pivot on excel or creating advanced views in a up-market OLAP tool, most of the usage of data in today’s world falls within the realm of Data Analysis/OLAP. It is essentially a post graduate course before you go for fellowship in Data Mining.

Chapters In Data Analysis/OLAP : -

Online Analytic Processing (OLAP)-Overview

This chapter provides the back-ground to the concept of OLAP and how it fits into the overall BI frame-work.

Advanced Data Analysis Types- Building Blocks

This chapter provides the advanced analysis capabilities within OLAP, which provides the building blocks for BI- End-User tools to fulfill contextual analysis requirements.

Business Hierarchies in OLAP and Data Warehouse

The subject of hierarchies is relevant to both OLAP and Enterprise Intelligence Delivery - Data Warehousing/Marting. Modeling of data is done, both in DW and OLAP, keeping the hierarchies in mind. However, OLAP is the platform where the hierarchies are manifested in their final shape for the purpose of analysis.

Additivity and Aggregation of Measures-Facts in OLAP Analysis

Additivity and correct aggregation methods application is fundamental to the success of Business Intelligence. The most common mistakes the modelers and designers make is on - Setting the Right Hierarchies AND Establishing Right Additivity and aggregation rules. You need to go through the chapter of business dimensional hierarchies, before you go through this chapter.