Extending Data Warehouses
Problem – Users Require Data From Outside the Data Warehouse
Enterprises and government agencies overwhelmed by scattered data silos and exponentially growing data volumes have deployed data warehouses to meet many of their reporting requirements. However a number of sources remain outside the warehouse. Providing users with complete business insight so they can achieve revenue, cost and risk management goals requires both:
- Historical data from the warehouse and up-to-the-minute data from transaction systems or operational data stores
- Summarized data from the warehouse and drill-down detail from transaction systems or operational data stores
- Internal data from the warehouse and external data from outside sources.
Solution – Use Data Virtualization to Extend Existing Data Warehouses
You can use Composite data virtualization to federate data warehouse data with additional sources, in effect extending existing data warehouse schemas and data. These complementary views let you add current data to historical warehouse data, detailed data to summarized warehouse data, external data to internal warehouse data, and more to quickly and easily work around the fact that key data your users need resides outside your consolidated data warehouse repositories.
In the integration pattern shown below, the Composite Information Server hosts new complementary views that integrate additional RDBMS and Web Service data sources as well extend an existing source, Packaged Applications.
Use Data Virtualization to Extend Existing Data Warehouse Schemas and Data
Selected Examples
- Combining Up-to-the-minute and Historical Data – To optimize deployment of repair crews and equipment across more than 10,000 production oil wells, an energy company uses Composite data virtualization to federate real-time crew, equipment, and well status data from the wells and SAP’s maintenance management system with historical surface, subsurface, and business data from the enterprise data warehouse. The net result is faster repairs which translate into more uptime and more revenue.
- Combining Internal and External Data – To analyze pharmaceutical sales and marketing effectiveness, this life sciences company uses Composite data virtualization to federate internal prescription sales data from their sales data warehouse with externally sourced competitor sales data from by a industry data services provider. This total market view enables more effective sales and marketing programs resulting in additional revenues.
