Bilir's Business Intelligence Portfolio SSAS Project

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Bilir's Business Intelligence Portfolio SSAS Project

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Bilir's Business Intelligence Portfolio SSAS Project

  1. 1. 5/3/2010<br />Figen Bilir ©<br />1<br />
  2. 2. Project Overview: AllWorks<br />The SSAS project was designed to build analysis package solutions using Analysis Services, setting the SQL database as the data source. <br />From the SQL Server database, build several custom views into the database and set up a series of cubes, dimensions and Key Point Indicators (KPIs) to analyze and measure AllWorks profitability and costs.<br /> Write MDX queries and display the KPIs in Excel.<br />5/3/2010<br />Figen Bilir ©<br />2<br />
  3. 3. Database Diagram<br />5/3/2010<br />Figen Bilir ©<br />3<br />
  4. 4. Design the Data Source View in BIDS<br />Restored the All Works Database from the Backup file. <br />Established database connection to SQL Server. <br />Use “Service Account” for login credentials. <br />Selected the fact tables and the dimension tables.<br />The DSV relationships were manually defined in order to complete the relationships between tables. Utilized the Data Source View (DSV) Diagram for All Works Data Source, defined the primary key - foreign key related members between tables.<br />5/3/2010<br />Figen Bilir ©<br />4<br />
  5. 5. Data Source View<br />5/3/2010<br />Figen Bilir ©<br />5<br />
  6. 6. Design the Cube in BIDS<br />Utilized the Cube Wizard to build the AllWorks Cube<br />Automatically created attributes and hierarchies <br />Verified that the Fact tables and Dimension Tables properly identified <br />Verified measures by measure group <br />Verified dimensions <br />Used Dimension Usage to verify dimensions used in each fact table <br />Edited AllWorks Calendar & Job Master dimensions with renaming levels and creating hierarchy<br />5/3/2010<br />Figen Bilir ©<br />6<br />
  7. 7. Job Master Dimension Design<br />Designed of the Job Master dimension structure including the attributes, hierarchies and logical view of the data for the dimension.<br />In this dimension there are two hierarchies, Client Groups and Client Geography, which efficiently organizes the data and allows the user to explore the data from a high level to a more detail level.<br />5/3/2010<br />Figen Bilir ©<br />7<br />
  8. 8. Job Master Dimension View<br />5/3/2010<br />Figen Bilir ©<br />8<br />
  9. 9. AllWorks Cube Structure<br />5/3/2010<br />Figen Bilir ©<br />9<br />
  10. 10. OLAP Partition Creation<br />You can divide cubes into partitions that represent how the data in the cube is used. Also OLAP partitioning is used in order to increase performance by placing data into different hard disk arrays. For example let’s say you have five years of data available, but that 80% of the queries are against the most recent year, and 20% are against the other four years. Put the most recent year in its own partition, and the remaining four years in a second partition. This way, you can select different aggregations for each partition, which will affect both performance and the size of the cube. <br />In AllWorks OLAP database one was created for up to and including 2005, and one for data 2006 and later. <br />5/3/2010<br />Figen Bilir ©<br />10<br />
  11. 11. OLAP Partition Creation cont’d<br />5/3/2010<br />Figen Bilir ©<br />11<br />Cube Partitioning is almost always done by a Time parameter. In this case data before 2006 is kept in a separate partition.<br />
  12. 12. OLAP Partition Creation cont’d<br />5/3/2010<br />Figen Bilir ©<br />12<br />Code for Partitions is written in T‐SQL. This code should be tested thoroughly in Management Studio (SSMS) before being implemented here.<br />
  13. 13. Design aggregations for a 50% performance increase<br />5/3/2010<br />Figen Bilir ©<br />13<br />
  14. 14. MDX Programming<br />All the functionality of MDX is available in Calculated Members and KPIs. You can create as many Calculated Members (also Named Sets) as you need. <br />MDX expressions are created and the formatting and look can be specified here.<br />5/3/2010<br />Figen Bilir ©<br />14<br />
  15. 15. MDX Query<br />5/3/2010<br />Figen Bilir ©<br />15<br />
  16. 16. MDX Query<br />5/3/2010<br />Figen Bilir ©<br />16<br />
  17. 17. MDX Query<br />5/3/2010<br />Figen Bilir ©<br />17<br />
  18. 18. MDX Query<br />5/3/2010<br />Figen Bilir ©<br />18<br />
  19. 19. KPIs for AllWorks<br />Key Performance Indicators (KPIs) are often evaluated over time and allows the business to analyze, examine and manage their predefined business goals. <br />The list of KPIs include comparison measures for Open Receivables, Growth in Jobs, Overhead Percent, Profit Percent and Overhead Category Percent. <br />Creating KPIs in SSAS involved: -Creating calculated members in the Calculations tab -Creating KPIs to use the calculated members -Testing the KPIs in an Excel spreadsheet.<br />5/3/2010<br />Figen Bilir ©<br />19<br />
  20. 20. Calculations for AllWorks<br />5/3/2010<br />Figen Bilir ©<br />20<br />
  21. 21. KPI creation for Open Receivables<br />5/3/2010<br />Figen Bilir ©<br />21<br />
  22. 22. Screenshot of KPI rendered in Excel for Open Receivables<br />5/3/2010<br />Figen Bilir ©<br />22<br />
  23. 23. KPI Creation for Quarterly Job Trend<br />5/3/2010<br />Figen Bilir ©<br />23<br />
  24. 24. Calculation for Quarterly Job Trend<br />5/3/2010<br />Figen Bilir ©<br />24<br />Two more calculation were created and used in the current one<br />
  25. 25. Screenshot of KPI rendered in Excel for Job Trend<br />5/3/2010<br />Figen Bilir ©<br />25<br />

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