Consolidating data warehouses
However, to gain a point-in-time visibility and understand the high-level operational aspects of any business, the historical data plays a vital role.With the emergence of matured Relational Database Management Systems (RDBMS) in 1960s, engineers across various enterprises started architecting ways to copy the data from the transactional systems over to different databases via manual or automated mechanism and use it for reporting and analysis.With Attunity, organizations can derive more value and insight from their data warehouse environment, improving agile analytics while minimizing cost and effort.
Attunity enables universal data availability by replicating, synchronizing, consolidating and ingesting data across all major data warehouse solutions.
This would require a lot of planning and architecture as typically; the banks are a conglomerate of many entities operating entirely independently at times and often crossing the geographical boundaries.
There are thousands of repositories where the data needs to be acquired and standardized in a format that it could be leveraged to obtain meaningful insights.
As the data in the transactional systems would get purged periodically, it would not be the case in these analytical repositories as their purpose was to store as much data as possible, hence the word “data warehouse” came into existence because these repositories would become a warehouse for the data.
Data Warehousing as a practice became very prominent during late 80s when the enterprises started building decision support systems that were mainly responsible to support reporting.