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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.

Data Lake 102
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Amazon DataZone now integrates with AWS Glue Data Quality and external data quality solutions

AWS Big Data

By analyzing the historical report snapshot, you can identify areas for improvement, implement changes, and measure the effectiveness of those changes. Ingest and analyze PySpark code In this section, we analyze the PySpark code that we use to perform data quality checks and send the results to Amazon DataZone.

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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).