Remove 2002 Remove Data Lake Remove Metrics
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Simplify data ingestion from Amazon S3 to Amazon Redshift using auto-copy

AWS Big Data

Now upload the files for transaction sold on 2002-12-31. Let’s run a query to get the daily total of sales transactions across all the stores in the US: SELECT ss_sold_date_sk, count(1) FROM store_sales GROUP BY ss_sold_date_sk; The output shown comes from the transactions sold on 2002-12-31.

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Use AWS Glue ETL to perform merge, partition evolution, and schema evolution on Apache Iceberg

AWS Big Data

As enterprises collect increasing amounts of data from various sources, the structure and organization of that data often need to change over time to meet evolving analytical needs. Schema evolution enables adding, deleting, renaming, or modifying columns without needing to rewrite existing data.

Snapshot 132
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Fine-grained access control in Amazon EMR Serverless with AWS Lake Formation

AWS Big Data

AWS is introducing general availability of fine-grained access control based on AWS Lake Formation for Amazon EMR Serverless on Amazon EMR 7.2. Enterprises can now significantly enhance their data governance and security frameworks. For instructions, refer to Create a data lake administrator.

Data Lake 105