Remove Data Lake Remove Metadata 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

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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Build a real-time analytics solution with Apache Pinot on AWS

AWS Big Data

Online Analytical Processing (OLAP) is crucial in modern data-driven apps, acting as an abstraction layer connecting raw data to users for efficient analysis. It organizes data into user-friendly structures, aligning with shared business definitions, ensuring users can analyze data with ease despite changes.

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Deploy real-time analytics with StarTree for managed Apache Pinot on AWS

AWS Big Data

StarTrees automatic data ingestion framework is ideal for enterprise workloads because it improves scalability and reduces the data maintenance complexity often found in open source Pinot deployments. The data is then modelled to help you organize and structure the data fetched from the selected data source into Pinot tables.