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This includes the ETL processes that capture source data, the functional refinement and creation of data products, the aggregation for business metrics, and the consumption from analytics, business intelligence (BI), and ML. The data warehouse is highly business critical with minimal allowable downtime.
This practice, together with powerful OLAP (onlineanalyticalprocessing) tools, grew into a body of practice that we call “business intelligence.” It seeks to optimize performance by identifying opportunities and challenges as soon as they emerge. Organizational agility requires robust, flexible systems.
Consultants and developers familiar with the AX data model could query the database using any number of different tools, including a myriad of different report writers. Data warehouses gained momentum back in the early 1990s as companies dealing with growing volumes of data were seeking ways to make analytics faster and more accessible.
As the first in-memory database for SAP, HANA was revolutionary, bringing together the best characteristics of both traditional online transaction processing and onlineanalyticalprocessing. BW does not provide reporting per se; it provides a data repository optimized for certain kinds of reporting.
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