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

Smart Data Collective

Data science is both a rewarding and challenging profession. One study found that 44% of companies that hire data scientists say the departments are seriously understaffed. Fortunately, data scientists can make due with fewer staff if they use their resources more efficiently, which involves leveraging the right tools.

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How gaming companies can use Amazon Redshift Serverless to build scalable analytical applications faster and easier

AWS Big Data

It includes business intelligence (BI) users, canned and interactive reports, dashboards, data science workloads, Internet of Things (IoT), web apps, and third-party data consumers. Popular consumption entities in many organizations are queries, reports, and data science workloads.

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The Future of AI in the Enterprise

Jet Global

Enterprise businesses cannot survive without robust data warehousing—data silos can rapidly devour money and resources, and any business still trying to make sense and cobble together ‘business intelligence’ from multiple reports and inconsistent data is rapidly going to lose ground to those businesses with integrated data and reporting.

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The Future of AI in the Enterprise

Jet Global

Enterprise businesses cannot survive without robust data warehousing—data silos can rapidly devour money and resources, and any business still trying to make sense and cobble together ‘business intelligence’ from multiple reports and inconsistent data is rapidly going to lose ground to those businesses with integrated data and reporting.

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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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How to Build a Performant Data Warehouse in Redshift

Sisense

First, we’ll dive into the two types of databases: OLAP (Online Analytical Processing) and OLTP (Online Transaction Processing). Think of it like something that houses the metrics used to power daily, weekly, or monthly business KPIs. roll-ups of many rows of data). Data architecture.

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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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