Remove Dashboards Remove Data Warehouse Remove Metrics Remove Online Analytical Processing
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How gaming companies can use Amazon Redshift Serverless to build scalable analytical applications faster and easier

AWS Big Data

Data lakes are more focused around storing and maintaining all the data in an organization in one place. And unlike data warehouses, which are primarily analytical stores, a data hub is a combination of all types of repositories—analytical, transactional, operational, reference, and data I/O services, along with governance processes.

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The Enterprise AI Revolution Starts with BI

Jet Global

Which problems do disparate data points speak to? And how can the data collected across multiple touchpoints, from retail locations to the supply chain to the factory be easily integrated? Enter data warehousing. So how is the data extracted?

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The Future of AI in the Enterprise

Jet Global

Which problems do disparate data points speak to? And how can the data collected across multiple touchpoints, from retail locations to the supply chain to the factory be easily integrated? Enter data warehousing. So how is the data extracted?

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The Future of AI in the Enterprise

Jet Global

Which problems do disparate data points speak to? And how can the data collected across multiple touchpoints, from retail locations to the supply chain to the factory be easily integrated? Enter data warehousing. So how is the data extracted?

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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. Business intelligence examples Reporting is a central facet of BI and the dashboard is perhaps the archetypical BI tool.

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How to Build a Performant Data Warehouse in Redshift

Sisense

This blog is intended to give an overview of the considerations you’ll want to make as you build your Redshift data warehouse to ensure you are getting the optimal performance. First, we’ll dive into the two types of databases: OLAP (Online Analytical Processing) and OLTP (Online Transaction Processing).

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Unleashing the power of Presto: The Uber case study

IBM Big Data Hub

To address their performance needs, Uber chose Presto because of its ability, as a distributed platform, to scale in linear fashion and because of its commitment to ANSI-SQL, the lingua franca of analytical processing. Uber chose Presto for the flexibility it provides with compute separated from data storage.

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