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Multi-Fact, Multi-Grain and Relative Dates - Defining Column Dependencies to Prevent Double Counting - Cognos Analytics Proven Practice (CAPP) Document

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Abstract

When analyzing business data within reports and visualizations, there is an issue known
as double counting that can arise in certain situations. Double counting can be
prevented by employing IBM Cognos Analytics data modeling to define column
dependencies for the business data. This document details the best practices to define
column dependencies given that there are various scenarios of table normalization in
the business data.

The document consists of the following sections:
1. Double Counting: Definition
2. Column Dependencies: Resolving Double Counting
3. Relative Date Analysis
4. Date Columns at Fact Grain: Resolving Double Counting
5. Best Practices: 1) Column Dependencies and 2) Date Columns at Fact Grain

Content

Please download the PDF below to view the document.

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Document Information

Modified date:
10 May 2019

UID

ibm10884168