Smart Infrastructure & Smart Applications for the Smart Business – Infrastructure & Application Performance Monitoring
Data Warehouse Automation & Real-time Data – Reducing Time to Value in a Distributed Analytical Environment
Creating Data Products in a Data Mesh, Data Lake or Lakehouse for Use in Analytics (9-10 June 2022, Stockholm)
Following on from my last blog on data federation, the next data federation pattern I would like to discuss is a Data Warehouse Holistic Data View pattern. This is as follows.
This pattern, also known as the schema extension pattern, uses data virtualization to create a holistic complete view of business activity by combining the latest most up to date operational transactional activity in one or more operational systems with detailed corresponding historical data from data warehouses and data marts.
Pattern Example Use Case
Front-office staff in a call centre operator or a branch of a bank may need to view current risk exposure for a customer they are on the phone to while also looking at a risk exposure trend for that customer across all loan products held. A second use case is regulatory compliance reporting whereby operational and historical data may both be needed for compliance reporting.
Reasons For Using It
This pattern allows companies to quickly show a holistic view of business activity that includes the more recent transactional activity combined with historical activity. This data can be presented for analysis and reporting even if the latest transactional data has not yet reached the data warehouse.
Look out for the next data federation data warehouse patterns on virtual data mart and virtual data source coming soon.