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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. This is critical for fast-moving enterprises to augment data structures to support new use cases. This hampers agility and time to insight.

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

AWS Big Data

Amazon Athena is a serverless, interactive analytics service built on open source frameworks, supporting open table file formats. Athena provides a simplified, flexible way to analyze petabytes of data where it lives. Analytics Architect on Amazon Athena. He has been working on query optimizers for over a decade.

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Themes and Conferences per Pacoid, Episode 8

Domino Data Lab

Data coming from machines tends to land (aka, data at rest ) in durable stores such as Amazon S3, then gets consumed by Hadoop, Spark, etc. Somehow, the gravity of the data has a geological effect that forms data lakes. DG emerges for the big data side of the world, e.g., the Alation launch in 2012.

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Generate security insights from Amazon Security Lake data using Amazon OpenSearch Ingestion

AWS Big Data

By converting logs and events using Open Cybersecurity Schema Framework , an open standard for storing security events in a common and shareable format, Security Lake optimizes and normalizes your security data for analysis using your preferred analytics tool. For more information, refer to Lifecycle management in Security Lake.

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Themes and Conferences per Pacoid, Episode 12

Domino Data Lab

Consider the following timeline: 2001 – Physics grad students are getting hired in quantity by hedge funds to work on Wall St. to join data science teams, e.g., to support advertising, social networks, gaming, and so on—I hired more than a few. 2018 – Global reckoning about data governance, aka “Oops!