presented by Marco Russo
[email protected] sqlbi.com sqlbi.com Who am I Latest conferences BI Expert and Consultant PASS Europe 2009 – Neuss – Germany Problem Solving Complex Project Assistance PASS 2009 – Seattle – USA DataWarehouse Assesments and Development SQL Conference 2010 – Milan – Italy Courses, Trainings and Workshops Teched 2010 – New Orleans – USA Microsoft Business Intelligence Partner Book Writer 24 Hours of PASS 2010 – Online PASS 2010 – Seattle – USA sqlbi.com Agenda DATA SOURCE (RELATIONAL MODELING) Relational Schema Decoupling Layer Dimensional Patterns Slowly Changing Dimensions Junk Dimensions Parent-Child Hierarchies Role Dimensions Drill-through Calculation Dimensions sqlbi.com sqlbi.com 1 CONFIGURATION Source OLTP DB SQLBI Methodology Relational Schema SNOWFLAKE SCHEMA Analysis Services reads data Mirror OLTP from Data Mart A Data Mart is not the Data Staging Area Warehouse ODS Data Warehouse Operational Data Store Data Marts OLAP Cubes Custom Reports Client Tools Other Systems Excel, Proclarity, … Customers Relational Schema Relational Schema STAR SCHEMA STAR VS. SNOWFLAKE SCHEMA Options for dimensions from snowflake schema: Transform into a star schema by using views Transform into a star schema by using DWV queries Join tables in SSAS dimensions Referenced Dimension Ideal solution Use SQL views to generate a star schema The star schema eliminates ambiguity Data Source Decoupling USE VIEWS TO DECOUPLE DIFFERENT LAYERS OF A BI SOLUTION DATA SOURCE (RELATIONAL MODELING) OLTP OLTP Mirror