Computing has evolved at an incredible pace. The first form of computer processing was batch. Later, OLTP (On-Line Transaction Processing) was born and allowed transactions to be recorded at the source of the transaction via terminals. Next, came OLCP (On-Line Complex Processing) that stormed the industry with complex queries. Now, powerful OLAP (On-Line Analytical Processing) functions provide data mining capabilities to discover a wealth of knowledge from the data.
When OLAP functions are combined with standard SQL within the data warehouse, they provide the ability to analyze large amounts of historical, business transactions from the past through the present. Plus, they provide the ability to project possible future values.
The OLAP functions are the cousins of the aggregate functions, but are very different in their use. Like traditional aggregates, OLAP functions operate on groups of rows and permit qualification and filtering of the group result. Unlike aggregates, OLAP functions also return the individual row detail data and not just the final aggregated value.
In demonstrating these capabilities both the ANSI and Teradata extensions are provided. It is up to the reader to decide which is most appropriate for a given situation.
The following charts contain the OLAP commands and their functions:
The Sales table below, is used in this chapter to demonstrate the OLAP functions:
Teradata Related Interview Questions
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Teradata Related Practice Tests
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|MYSQL DBA Practice Tests||Database Administration Practice Tests|
|DB2 SQL Programming Practice Tests||Hadoop Administration Practice Tests|
Teradata Parallel Architecture
Fundamental Sql Using Select
On-line Help And Show Commands
Date And Time Processing
Character String Processing
Reporting Totals And Subtotals
Data Definition Language
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