A Data Store Independent of Consistency Models, Upfront Data Modeling and Access Algorithms
Tina Groves1 in “Where Does Hadoop Fit in a Business Intelligence Data Strategy?“:
For example, the decision to move and transform operational data to an operational data store (ODS), to an enterprise data warehouses (EDW) or to some variation of OLAP is often made to improve performance or enhance broad consumability by business people, particularly for interactive analysis. Business rules are needed to interpret data and to enable BI capabilities such as drill up/drill down. The more business rules built into the data stores, the less modelling effort needed between the curated data and the BI deliverable.
That’s why Chirag Mehta’s ideal database featuring “an ubiquitous interface independent of consistency models, upfront data modeling, and access algorithms” is never going to be efficient. Actually, I’m not even sure it would make sense being built.
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Tina Groves: Product Strategist, IBM Business Intelligence ↩
Original title and link: A Data Store Independent of Consistency Models, Upfront Data Modeling and Access Algorithms (©myNoSQL)
via: http://www.ibmbigdatahub.com/blog/where-does-hadoop-fit-business-intelligence-data-strategy
