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Data Modeling for Business Intelligence with Microsoft SQL Server: Modeling a Data Warehouse
October 2008
(Based on 6 reviews)
For decades, businesses of all shapes and sizes have been storing their historical data. Everything from cash register rolls stored in filing cabinets to web application transactions being stored in relational databases have been sitting quietly, often collecting dust, just waiting for someone to dispose of them. Fortunately, as we’ve transitioned from paper based records to computer based records, we’ve discovered that mining this historical data can yield a veritable gold mine of information that can help guide a business towards future success. Understanding everything from geographical product preferences to age based sales demographics to employee performance can help companies make smart decisions about what they sell, and how they sell it. Today, we can use modern technology such as Microsoft SQL Server to run both the transactional databases that support our mission critical applications as well as the analytical databases that can help drive our businesses forward.
In this whitepaper, we’ll look at how to use traditional data modeling techniques to build a data model for a data warehouse, as well as how to implement a data warehouses and their accompanying processing loads. We’ll also look at CA’s ERwin Data Modeler to expedite and improve upon traditional design methodology.
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