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Tag archive for ‘Purchasing Data Warehouse’

After we have created the dimension tables and the fact table and populated them with data the final step to getting a star schema is of course to actually join the dimension tables to the fact table. In the datamartist tool we do this with a Join block. Check out the first four parts of […]

  • Joining the Dimension Table to the Fact Table- Purchasing Data mart (Part 5)

    After we have created the dimension tables and the fact table and populated them with data the final step to getting a star schema is of course to actually join the dimension tables to the fact table. In the datamartist tool we do this with a Join block. Check out the first four parts of […]

  • Hierarchies and Tree Structures in Dimensions- an Example Item Dimension (Part 4)

    Having a way to create and manage tree structures (Hierarchies) with your dimension and fact tables is a key part of making a dimensional model in any data warehouse or data mart. Hierarchical structures lend themselves to managing a very large number of categories and we use them to create drill down paths. Check out […]

  • Connecting the dimension table to the fact table- Vendor Example (Part 3)

    In parts one and two of this series we introduced our challenge (to make a data mart to analyze the Acme Company's spending) and showed how the Datamartist tool could import millions of rows of data and then turn it into a fact table we can use in Excel. Now we need to create a […]

  • Creating a Fact Table with the Vendor dimension Purchasing DM (Part 2)

    In creating a data warehouse or data mart data model there are two key types of tables- fact tables and dimension tables. Fact tables hold the data to be analyzed, dimensional tables provide categories and analysis values that organize the data. So we have our mission from Part 1: to analyze the "Acme does everything" […]

  • Purchasing Data Mart – cutting costs with analysis (Part 1)

    In these difficult economic times, cutting costs isn't just optimization, it's survival. You can't reduce what you can't quantify so it's critical to analyze the accounts payable (AP), or purchasing data to identify the areas where cost savings are possible. This is one of the most useful financial data marts because spending is often something […]