Remove Metrics Remove Modeling Remove Online Analytical Processing
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What Are OLAP (Online Analytical Processing) Tools?

Smart Data Collective

Online analytical processing is a computer method that enables users to retrieve and query data rapidly and carefully in order to study it from a variety of angles. Online Analytical Processing (OLAP) is a term that refers to the process of analyzing data online. Using OLAP Tools Properly.

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What is business intelligence? Transforming data into business insights

CIO Business Intelligence

The potential use cases for BI extend beyond the typical business performance metrics of improved sales and reduced costs. BI focuses on descriptive analytics, data collection, data storage, knowledge management, and data analysis to evaluate past business data and better understand currently known information.

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The Enterprise AI Revolution Starts with BI

Jet Global

Many of the features frequently attributed to AI in business, such as automation, analytics, and data modeling aren’t actually features of AI at all. Cubes are multi-dimensional datasets that are optimized for analytical processing applications such as AI or BI solutions. So how is the data extracted?

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

Sisense

Typically, this involves using statistical analysis and predictive modeling to establish trends, figuring out why things are happening, and making an educated guess about how things will pan out in the future. What About “Business Intelligence”? BI is also about accessing and exploring your organization’s data.

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Unleashing the power of Presto: The Uber case study

IBM Big Data Hub

This blog takes you on a journey into the world of Uber’s analytics and the critical role that Presto, the open source SQL query engine, plays in driving their success. Uber’s DNA as an analytics company At its core, Uber’s business model is deceptively simple: connect a customer at point A to their destination at point B.

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Build a real-time analytics solution with Apache Pinot on AWS

AWS Big Data

Online Analytical Processing (OLAP) is crucial in modern data-driven apps, acting as an abstraction layer connecting raw data to users for efficient analysis. Business metrics – Providing KPIs, scorecards, and business-relevant benchmarks. Anomaly detection – Identifying outliers or unusual behavior patterns.

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Unlock scalability, cost-efficiency, and faster insights with large-scale data migration to Amazon Redshift

AWS Big Data

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. KPIs evaluate the operational metrics, cost metrics, and end-user response time metrics.