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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. These types of queries are suited for a data warehouse. Amazon Redshift is fully managed, scalable, cloud data warehouse.

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How the Edge Is Changing Data-First Modernization

CIO Business Intelligence

From the factory floor to online commerce sites and containers shuttling goods across the global supply chain, the proliferation of data collected at the edge is creating opportunities for real-time insights that elevate decision-making. The concept of the edge is not new, but its role in driving data-first business is just now emerging.

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Build a serverless transactional data lake with Apache Iceberg, Amazon EMR Serverless, and Amazon Athena

AWS Big Data

They enable transactions on top of data lakes and can simplify data storage, management, ingestion, and processing. These transactional data lakes combine features from both the data lake and the data warehouse. One important aspect to a successful data strategy for any organization is data governance.

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Five actionable steps to GDPR compliance (Right to be forgotten) with Amazon Redshift

AWS Big Data

Organizations must comply with these requests provided that there are no legitimate grounds for retaining the personal data, such as legal obligations or contractual requirements. Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. Tags provide metadata about resources at a glance.

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Enrich your customer data with geospatial insights using Amazon Redshift, AWS Data Exchange, and Amazon QuickSight

AWS Big Data

Load generic address data to Amazon Redshift Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. Redshift Serverless makes it straightforward to run analytics workloads of any size without having to manage data warehouse infrastructure.

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How Amazon Devices scaled and optimized real-time demand and supply forecasts using serverless analytics

AWS Big Data

This introduces the need for both polling and pushing the data to access and analyze in near-real time. Implementation strategy Based on these requirements, we changed strategies and started analyzing each issue to identify the solution. Clients access this data store with an API’s.

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Simplify operational data processing in data lakes using AWS Glue and Apache Hudi

AWS Big Data

The Analytics specialty practice of AWS Professional Services (AWS ProServe) helps customers across the globe with modern data architecture implementations on the AWS Cloud. Table data storage mode – There are two options: Historical – This table in the data lake stores historical updates to records (always append).