Data warehousing has become a fundamental component of the enterprise’s data architecture. It provides a means to store massive amounts of data to enable a wide variety of analytics, from historical reporting to business intelligence.
A key issue encountered in data warehousing is updating the large data store with current data changes. For example, a correction made to a trade performed ten (10) days ago can cascade down to over a million data points in a data warehouse — all the data dependent on that trade, from position updates to reporting. Such updates can be very time consuming and taxing on the resources of a data warehouse.
Princeton Financial Systems provides its InfoHub product as the primary means of updating a data warehouse. It uses the publish-subscribe methodology for queuing database updates. However, this has proven to be very slow and cumbersome. Through technology similar to that found in products like Imperva, InfoTilt offers a suite of products, including PAM Messenger Notifier, to address demands for real-time or near real-time PAM data warehouse updates.