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Building your first AS solution

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Ivan Donev
Ivan Donev

Presentation for the Bulgarian .NET and BI user group

Technology
1 of 13
OLAP Services 7.0 • 1998 (Plato) AS 2000 • 2000 (Shiloh) AS 2005 • 2005 (Yukon) AS 2008 • 2008 (Katmai) AS 2012 • 2012 (Denali) • Tabular/MD
Product Aggregation of sales value by product, customer, and time • Multidimensional analysis is based on cubes whose core components are measures and dimensions • OLAP cubes have aggregations precalculated during processing
Multidimensional models
Dimension Attributes Dimension Dimension Attributes Attributes Fact Measures Star schema Dimension Dimension Attributes Snowflake schema Dimension Attributes Attributes
Analysis Services Database Cube A Cube B Cube C Dimension Data Source Security Measure groups Measures
2013 integrated
Building your first AS solution

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Building your first AS solution

Editor's Notes

  1. This topic should be revision for most students. Use it to ensure that all students have a basic understanding of the star schema design used in dimensional data warehouses.Review the articles referenced in the student notes in case students want to better understand how the star join query optimizations in the SQL Server query optimizer work. However, emphasize that the optimizations are automatic and that students do not need to do anything other than use a star schema for the data warehouse tables to benefit from them.