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Enhance monitoring and debugging for AWS Glue jobs using new job observability metrics

AWS Big Data

For any modern data-driven company, having smooth data integration pipelines is crucial. These pipelines pull data from various sources, transform it, and load it into destination systems for analytics and reporting. The end benefit for you is more effective and optimized AWS Glue for Apache Spark workloads.

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AWS Glue Data Quality is Generally Available

AWS Big Data

We are excited to announce the General Availability of AWS Glue Data Quality. Our journey started by working backward from our customers who create, manage, and operate data lakes and data warehouses for analytics and machine learning. You can then augment recommendations with out-of-the-box data quality rules.

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An AI Chat Bot Wrote This Blog Post …

DataKitchen

Observability in DataOps refers to the ability to monitor and understand the performance and behavior of data-related systems and processes, and to use that information to improve the quality and speed of data-driven decision making. Overall, DataOps observability is an essential component of modern data-driven organizations.

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Query your Iceberg tables in data lake using Amazon Redshift (Preview)

AWS Big Data

Amazon Redshift enables you to directly access data stored in Amazon Simple Storage Service (Amazon S3) using SQL queries and join data across your data warehouse and data lake. With Amazon Redshift, you can query the data in your S3 data lake using a central AWS Glue metastore from your Redshift data warehouse.

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Introducing Apache Hudi support with AWS Glue crawlers

AWS Big Data

Apache Hudi is an open table format that brings database and data warehouse capabilities to data lakes. Apache Hudi helps data engineers manage complex challenges, such as managing continuously evolving datasets with transactions while maintaining query performance. For CoW tables, queries see the latest data committed.

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Turning the page

Cloudera

Our customers must also have secure access to their data from anywhere – from on-premises to hybrid clouds and multiple public clouds. We must integrate and optimize the end-to-end data lifecycle for our customers, empowering them to focus on what really matters – extracting value from their data.

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How AWS helped Altron Group accelerate their vision for optimized customer engagement

AWS Big Data

The AWS Glue crawler populates the table definition with its schema in AWS Glue Data Catalog. Foundations for a data lake with data governance controls and data quality checks. The Altron team created an AWS Glue crawler and configured it to run against Azure SQL to discover its tables.