- The World in Transition
- What Was: The Data Warehouse Is the Historical Record
- What Is: Bypassing the Data Warehouse
- What If: The Data Warehouse Becomes the Foundation for Collaboration
- Updating the Data Warehouse from Analytic Applications
- Putting It All Together
Updating the Data Warehouse from Analytic Applications
The data warehouse has been limited to one-way transportation of information. Data moves from operational systems into the data warehouse via the ETL process. From the data warehouse, data is transported to users via business intelligence technologies. A key concept of predictive intelligence is that the analytic applications are a collection point of data that also should be managed in the data warehouse. The applications are adding new facts and measures that conform to the language standard of the data warehouse.
By managing the data from predictive intelligence in the data warehouse, critically important business goals and performance benchmarks are available to calibrate performance. Sophisticated agent processes can be employed to alert users when there is a need for action. Is it more important to know what was in inventory over the last 12 weeks, what is in inventory now, or when you will run out of inventory (if)?