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Apache Iceberg optimization: Solving the small files problem in Amazon EMR

AWS Big Data

Iceberg tables store metadata in manifest files. As the number of data files increase, the amount of metadata stored in these manifest files also increases, leading to longer query planning time. The query runtime also increases because it’s proportional to the number of data or metadata file read operations.

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

AWS Big Data

Data management and governance Addressing the challenges mentioned requires a combination of technical, operational, and legal measures. Tagging Consider tagging your Amazon Redshift resources to quickly identify which clusters and snapshots contain the PII data, the owners, the data retention policy, and so on.

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Modernize a legacy real-time analytics application with Amazon Managed Service for Apache Flink

AWS Big Data

Frequent materialized view refreshes on top of constantly changing base tables due to streamed data can lead to snapshot isolation errors. The second streaming data source constitutes metadata information about the call center organization and agents that gets refreshed throughout the day.

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How OLX Group migrated to Amazon Redshift RA3 for simpler, faster, and more cost-effective analytics

AWS Big Data

To do this, we required the following: A reference cluster snapshot – This ensures that we can replay any tests starting from the same state. A set of queries from the production cluster – This set can be reconstructed from the Amazon Redshift logs ( STL_QUERYTEXT ) and enriched by metadata ( STL_QUERY ). Take measurements 18 x DC2.

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Power enterprise-grade Data Vaults with Amazon Redshift – Part 2

AWS Big Data

Chargeback metadata Amazon Redshift provides different pricing models to cater to different customer needs. Automated backup Amazon Redshift automatically takes incremental snapshots that track changes to the data warehouse since the previous automated snapshot. Automatic WLM manages the resources required to run queries.

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Blending Art and Science: Using Data to Forecast and Manage Your Sales Pipeline

Sisense

For sales leaders, what’s hugely empowering is the ability to slice and dice data on the fly, understand what team and individual reps should be achieving, and easily measure the team from a data driven standpoint. Daily snapshot of opportunities that’s derived from a table of opportunities’ histories. Calculate opportunity metadata 5.

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What Is Data Intelligence?

Alation

It includes intelligence about data, or metadata. The earliest DI use cases leveraged metadata — EG, popularity rankings reflecting the most used data — to surface assets most useful to others. Again, metadata is key. Data Intelligence and Metadata. Data intelligence is fueled by metadata.