Chapter 1: Business Intelligence overview
by Calisto Zuzarte, Virginia Totanes, Nicholas Summers, Paul Read, Daniela Momirosk
DB2 UDB's High-Function Business Intelligence in e-business
- Figures
- Tables
- Examples
- Notices
- Preface
- Chapter 1: Business Intelligence overview
- Chapter 2: DB2 UDB’s materialized views
- Materialized view overview
- Materialized view CREATE considerations
- Materialized view maintenance considerations
- Loading base tables (LOAD utility)
- Materialized view ALTER considerations
- Materialized view DROP considerations
- Materialized view matching considerations
- Materialized view design considerations
- Step 1: Collect queries & prioritize
- Step 2: Generalize local predicates to GROUP BY
- Step 3: Create the materialized view
- Step 4: Estimate materialized view size
- Step 5: Verify query routes to “empty” the materialized view
- Step 6: Consolidate materialized views
- Step 7: Introduce cost issues into materialized view routing
- Step 8: Estimate performance gains
- Step 9: Load the materialized views with production data
- Generalizing local predicates application example
- Materialized view tuning considerations
- Refresh optimization
- Materialized view limitations
- Replicated tables in nodegroups
- Chapter 3: DB2 UDB’s statistics, analytic, and OLAP functions
- DB2 UDB’s statistics, analytic, and OLAP functions
- Statistics and analytic functions
- OLAP functions
- Ranking, numbering and aggregation functions (1/2)
- Ranking, numbering and aggregation functions (2/2)
- GROUPING capabilities ROLLUP & CUBE
- Ranking, numbering, aggregation examples (1/3)
- Ranking, numbering, aggregation examples (2/3)
- Ranking, numbering, aggregation examples (3/3)
- GROUPING, GROUP BY, ROLLUP and CUBE examples (1/3)
- GROUPING, GROUP BY, ROLLUP and CUBE examples (2/3)
- GROUPING, GROUP BY, ROLLUP and CUBE examples (3/3)
- Chapter 4: Statistics, analytic, OLAP functions in business scenarios
- Introduction
- Retail
- Present annual sales by region and city
- Provide total quarterly and cumulative sales revenues by year
- List the top 5 sales persons by region this year
- Compare and rank the sales results by state and country
- Determine relationships between product purchases
- Determine the most profitable items and where they are sold
- Identify store sales revenues noticeably different from average
- Finance
- Identify the most profitable customers
- Identify the profile of transactions concluded recently
- Identify target groups for a campaign
- Evaluate effectiveness of a marketing campaign (1/2)
- Evaluate effectiveness of a marketing campaign (2/2)
- Identify potential fraud situations for investigation
- Plot monthly stock prices movement with percentage change
- Plot the average weekly stock price in September
- Project growth rates of Web hits for capacity planning purposes
- Relate sales revenues to advertising budget expenditures
- Sports
- Appendix A: Introduction to statistics and analytic concepts
- Appendix B: Tables used in the examples
- Appendix C: Materialized view syntax elements
- Related publications
- Index (1/2)
- Index (2/2)
- Back cover
© Copyright IBM Corp. 2002 1
Chapter 1. Business Intelligence
overview
In this chapter we provide an overview of IBM’s Business Intelligence strategy
and offerings. We position the contents of this document with respect to the
overall solution.
The topics covered include:
? e-business drivers
? IBM’s BI strategy and offerings
? Redbook focus
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