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

AWS Big Data

This post provides guidance on how to build scalable analytical solutions for gaming industry use cases using Amazon Redshift Serverless. Flexible and easy to use – The solutions should provide less restrictive, easy-to-access, and ready-to-use data. A data warehouse is one of the components in a data hub.

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

Jet Global

For more sophisticated multidimensional reporting functions, however, a more advanced approach to staging data is required. The Data Warehouse Approach. 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.

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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. Which problems do disparate data points speak to? Enter data warehousing. So how is the data extracted?

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

Jet Global

First, accounting moved into the digital age and made it possible for data to be processed and summarized more efficiently. Spreadsheets enabled finance professionals to access data faster and to crunch the numbers with much greater ease. Today’s technology takes this evolution a step further.

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What Role Does Data Mining Play for Business Intelligence?

Jet Global

Business intelligence (BI) software can help by combining online analytical processing (OLAP), location intelligence, enterprise reporting, and more. If data is the fuel driving opportunities for optimization, data mining is the engine—converting that raw fuel into forward motion for your business. READ BLOG POST.

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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?