Our approach to building a Data Warehouse is to develop a "proof-of-concept" model. This model is then used to further evaluate how and in what circumstances the data is used to provide information. The next step is to determine what can be summary tables and what kinds of questions will require access at the lowest data levels.

We use Oracle Data Mining to build predictive Models and develop Profile and Cluster and  Anomaly Detection Models.

We have used custom scripting in PL/SQL, Data Warehouse Builder and Informatica for Data Integration. 

Key Benefits

• If we can model it we can build it
• Incremental approach
• Knowledge of the Data and its usage and source
• Predictive Modelling
• Profiling
• Cluster Models
• Anomaly Models

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Last modified: October 15, 2010