Model updating using operational data
Considerable effort was invested by some companies to consolidate a multitude of RTBI systems into a single ODS supporting enterprise-wide tactical and strategic decision-making or enterprise content management (ECM), shown as the final step in Figure 2.
The cost and disruption imposed by conversion to an ODS has so far resulted in little progress in expanding RTBI systems to support both tactical and strategic decision-making for any particular corporate function, much less the enterprise.
Another particular ODS characteristic is that it is bi-directional.
Unlike a data warehouse, which typically only accepts information from enterprise systems, an ODS both accepts information from and delivers information to the other enterprise systems.
The advantages of such integration are clear: The bottom line is that today, companies are achieving RTBI by directly integrating their systems using real-time heterogeneous data replication, or they are trickle-feeding data marts in real-time and using these marts to gather information.
These warehouses or application networks may or may not turn into an ODS as consolidation occurs.
On the one hand, it must be able to respond to complex queries from knowledge users, data-mining facilities, and rules engines using online analytical processing (OLAP).
The database structures suitable for OLAP are characterized by fat keys that allow rapid searching of the database to respond to complex queries.
If one system changes this data item, the ODS acts as a central data repository that informs the other systems of the new data value so they update their databases.
Other examples of outgoing information are the results of the rules engine.
An operational data store (ODS) is a type of database that's often used as an interim logical area for a data warehouse.