Considering data processing as a central component of data management and on a par with databases offers new insights on how to improve overall efficiency and return on investment in traditional data warehouses.
For the last 30 or so years, the precursor to most large scale business intelligence (BI) environments has been the Enterprise Data Warehouse (EDW). A data warehouse (DW) is usually a central database (DB) for reporting, planning, and analyzing summarized, subject-matter data integrated from disparate, historical transaction sources.
The traditional or enterprise data warehouse (EDW) has been at the center of data’s transformation to business intelligence (BI) for years. An EDW involves a centralized data repository (traditionally, a relational database) from which data marts and reports are built.