In many organizations, a data warehouse is the only system where data from numerous and disparate operational sources has been integrated into a single repository of enterprise data.
The rapid delivery of a single system of record containing fully integrated and historical data to be used as the source for most of the enterprise’s reporting and decision support needs has long been the rallying cry and promise of the data warehouse.
In many organizations, a data warehouse is the only system where data from numerous and disparate operational sources has been integrated into a single repository of enterprise data.
The rapid delivery of a single system of record containing fully integrated and historical data to be used as the source for most of the enterprise’s reporting and decision support needs has long been the rallying cry and promise of the data warehouse.
However, I have witnessed beautifully architected, elegantly implemented, and diligently maintained data warehouses simply get ignored by the organization, which continues to rely on its data silos and spreadsheets for reporting and decision making.
The most common reason is that these big boxes of data are often built with little focus on the quality of the data being delivered.
But that’s just my opinion based on my personal experience. So let’s conduct an unscientific poll.
Additionally, please feel free to post a comment below and explain your vote or simply share your opinions and experiences.
