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

AWS Big Data

A data hub contains data at multiple levels of granularity and is often not integrated. It differs from a data lake by offering data that is pre-validated and standardized, allowing for simpler consumption by users. Data hubs and data lakes can coexist in an organization, complementing each other.

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TIBCO JasperSoft for BI and Reporting

BizAcuity

TIBCO Jaspersoft offers a complete BI suite that includes reporting, online analytical processing (OLAP), visual analytics , and data integration. The web-scale platform enables users to share interactive dashboards and data from a single page with individuals across the enterprise. Data Security.

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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.

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Master Your Power BI Environment with Tabular Models

Jet Global

As a security measure, Microsoft is closing off direct database access to live Microsoft Dynamics ERP data. The company is pointing customers to several other options, including “BYOD” (which stands for “bring your own database”) and Microsoft Azure data lakes. This leads to the second option, which is a data warehouse.

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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. Liat Tzur is a Senior Technical Account Manager at Amazon Web Services.

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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

Uber understood that digital superiority required the capture of all their transactional data, not just a sampling. They stood up a file-based data lake alongside their analytical database. Uber chose Presto for the flexibility it provides with compute separated from data storage.

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