Remove Analytics Remove Online Analytical Processing Remove Structured Data Remove Technology
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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

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. Today, data lakes are still an evolving technology aimed at solving a very different problem than financial reporting.

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Business Intelligence Solutions: Every Thing You Need to Know

FineReport

Data is the key to gaining great insights for most businesses, but it is also one of the biggest obstacles. Originally, Excel has always been the “solution” for various reporting and data needs. Technicals such as data warehouse, online analytical processing (OLAP) tools, and data mining are often binding.

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How Aura from Unity revolutionized their big data pipeline with Amazon Redshift Serverless

AWS Big Data

Amazon Redshift is a recommended service for online analytical processing (OLAP) workloads such as cloud data warehouses, data marts, and other analytical data stores. We explore why Aura chose this solution and what technological challenges it helped solve.