Remove Analytics Remove Data Lake Remove Online Analytical Processing Remove Optimization
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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. Data Lakes. Traditional databases and data warehouses do not lend themselves to that task.

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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. They should also provide optimal performance with low or no tuning.

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How OLAP and AI can enable better business

IBM Big Data Hub

Online analytical processing (OLAP) database systems and artificial intelligence (AI) complement each other and can help enhance data analysis and decision-making when used in tandem. Early OLAP systems were separate, specialized databases with unique data storage structures and query languages.

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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. These campaigns are optimized by using an AI-based bid process that requires running hundreds of analytical queries per campaign.

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Build an Amazon Redshift data warehouse using an Amazon DynamoDB single-table design

AWS Big Data

A key pillar of AWS’s modern data strategy is the use of purpose-built data stores for specific use cases to achieve performance, cost, and scale. Deriving business insights by identifying year-on-year sales growth is an example of an online analytical processing (OLAP) query.

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Unleashing the power of Presto: The Uber case study

IBM Big Data Hub

But what most people don’t realize is that behind the scenes, Uber is not just a transportation service; it’s a data and analytics powerhouse. Every day, millions of riders use the Uber app, unwittingly contributing to a complex web of data-driven decisions. But the simplicity ends there. What is Presto?

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