Transforming data into valuable information your enterprise can use sometimes is a daunting task. However, it doesn’t have to be.
In a recent DBTA webinar, Donald Soulsby, VP architecture strategies at Sandhill Consultant, and Jeff Harris, technical services manager at Sandhill Consultant, discussed how to survive and thrive with data intelligence.
Soulsby and Harris’ approach is built on the notion that information is based on point over time (POT) data transformed from point in time (PIT) data, using erwin Data Modeler, Global IDs' Information Management Suite and Sandhill Consultants' education and product enhancement offerings.
Data warehouse architecture can range from top-down to bottom up to hybrid, according to Soulsby and Harris.
An Enterprise Data Warehouse is a subject oriented, integrated, non volatile and time variant collection of data in support of management’s decisions. In the data warehouse, information is stored in 3rd normal form. Data warehouse is the conglomerate of all data marts within the enterprise. Information is always stored in the dimensional model.
The Data Vault Model is a detail oriented, historical tracking and uniquely linked set of normalized tables that support one or more functional areas of business. It is a hybrid approach encompassing the best of breed between 3rd normal form (3NF) and star schema. The design is flexible, scalable, consistent and adaptable to the needs of the enterprise.
Users can get started by figuring out where they are and identifying and classifying atomic data. The next step is to secure enterprise governance and figure out where to go from there.
An archived on-demand replay of this webinar is available here.