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How OLAP and AI can enable better business

IBM Big Data Hub

Online analytical processing (OLAP) database systems and artificial intelligence (AI) complement each other and can help enhance data analysis and decision-making when used in tandem. As AI techniques continue to evolve, innovative applications in the OLAP domain are anticipated.

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Navigating Data Entities, BYOD, and Data Lakes in Microsoft Dynamics

Jet Global

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. Online analytical processing (OLAP), which enabled users to quickly and easily view data along different dimensions, was coming of age.

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Financial Intelligence vs. Business Intelligence: What’s the Difference?

Jet Global

This practice, together with powerful OLAP (online analytical processing) tools, grew into a body of practice that we call “business intelligence.” Past performance and current conditions are critically important; but without a view to the road ahead, business leaders risk being blindsided by unexpected developments.

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Unleashing the power of Presto: The Uber case study

IBM Big Data Hub

Large, untested workloads run the risk of hogging all the resources. As a result, they continue to expand their use cases to include ETL, data science , data exploration, online analytical processing (OLAP), data lake analytics and federated queries. EMA Technical Case Study, sponsored by Ahana.

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