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Enhance query performance using AWS Glue Data Catalog column-level statistics

AWS Big Data

Today, we’re making available a new capability of AWS Glue Data Catalog that allows generating column-level statistics for AWS Glue tables. These statistics are now integrated with the cost-based optimizers (CBO) of Amazon Athena and Amazon Redshift Spectrum , resulting in improved query performance and potential cost savings.

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Maximize your data dividends with active metadata

IBM Big Data Hub

Metadata management performs a critical role within the modern data management stack. However, as data volumes continue to grow, manual approaches to metadata management are sub-optimal and can result in missed opportunities. This puts into perspective the role of active metadata management. What is Active Metadata management?

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Run Trino queries 2.7 times faster with Amazon EMR 6.15.0

AWS Big Data

Benchmark setup In our testing, we used the 3 TB dataset stored in Amazon S3 in compressed Parquet format and metadata for databases and tables is stored in the AWS Glue Data Catalog. Table and column statistics were not present for any of the tables. and later, S3 file metadata-based join optimizations are turned on by default.

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The Future of Data Lineage and the Role of Metadata

Alation

Active metadata will play a critical role in automating such updates as they arise. I’ve adopted the statistics related terminology of deterministic and non-deterministic to help define and explain each. If a language can include metadata in the form of comments (and they all can) then markup can be inserted.

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Use Apache Iceberg in your data lake with Amazon S3, AWS Glue, and Snowflake

AWS Big Data

Iceberg tables maintain metadata to abstract large collections of files, providing data management features including time travel, rollback, data compaction, and full schema evolution, reducing management overhead. Snowflake writes Iceberg tables to Amazon S3 and updates metadata automatically with every transaction.

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Why Metadata Management Automation is Crucial to the Healthcare Industry

Octopai

And healthcare providers of all kinds are often required to provide data, properly cleansed of identifying patient information, for government agencies to compile national healthcare statistics. Data Governance Starts With Metadata Management. Good Healthcare Metadata Management Requires Good Tools. Schedule a demo today.

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Speed up queries with the cost-based optimizer in Amazon Athena

AWS Big Data

Starting today, the Athena SQL engine uses a cost-based optimizer (CBO), a new feature that uses table and column statistics stored in the AWS Glue Data Catalog as part of the table’s metadata. By using these statistics, CBO improves query run plans and boosts the performance of queries run in Athena.