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The Enterprise AI Revolution Starts with BI

Jet Global

But the vast reams of data generated daily are presenting a new problem for businesses—what data matters? The optimized data warehouse isn’t simply a number of relational databases cobbled together, however—it’s built on modern data storage structures such as the Online Analytical Processing (or OLAP) cubes.

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The Future of AI in the Enterprise

Jet Global

But the vast reams of data generated on a daily basis are presenting a new problem for businesses—what data matters? The optimized data warehouse isn’t simply a number of relational databases cobbled together, however—it’s built on modern data storage structures such as the Online Analytical Processing (or OLAP) cubes.

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What’s the Difference Between Business Intelligence and Business Analytics?

Sisense

BI lets you apply chosen metrics to potentially huge, unstructured datasets, and covers querying, data mining , online analytical processing ( OLAP ), and reporting as well as business performance monitoring, predictive and prescriptive analytics. But on the whole, BI is more concerned with the whats and the hows than the whys.

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The Future of AI in the Enterprise

Jet Global

But the vast reams of data generated on a daily basis are presenting a new problem for businesses—what data matters? The optimized data warehouse isn’t simply a number of relational databases cobbled together, however—it’s built on modern data storage structures such as the Online Analytical Processing (or OLAP) cubes.

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What is business intelligence? Transforming data into business insights

CIO Business Intelligence

BI tools access and analyze data sets and present analytical findings in reports, summaries, dashboards, graphs, charts, and maps to provide users with detailed intelligence about the state of the business. The potential use cases for BI extend beyond the typical business performance metrics of improved sales and reduced costs.

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Welcome To The Digital Age: BI Meets Social Media

Smart Data Collective

In the 1990s, OLAP tools allowed multidimensional data analysis. Engagement metrics, such as likes, comments, shares, and click-through rates, provide insights into how audiences interact with content. From sentiment analysis to tracking engagement metrics, the potential for enhancing customer insights with social data is boundless.

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Unleashing the power of Presto: The Uber case study

IBM Big Data Hub

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. The power of Presto in Uber’s data-driven journey Today, Uber relies on Presto to power some impressive metrics.

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