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Amazon Q data integration adds DataFrame support and in-prompt context-aware job creation

AWS Big Data

Amazon Q data integration , introduced in January 2024, allows you to use natural language to author extract, transform, load (ETL) jobs and operations in AWS Glue specific data abstraction DynamicFrame. In this post, we discuss how Amazon Q data integration transforms ETL workflow development.

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Data Integrity, the Basis for Reliable Insights

Sisense

Uncomfortable truth incoming: Most people in your organization don’t think about the quality of their data from intake to production of insights. However, as a data team member, you know how important data integrity (and a whole host of other aspects of data management) is. What is data integrity?

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Complex Data Transformations — Test Planning Best Practices

Wayne Yaddow

Complex Data TransformationsTest Planning Best Practices Ensuring data accuracy with structured testing and best practices Photo by Taylor Vick on Unsplash Introduction Data transformations and conversions are crucial for data pipelines, enabling organizations to process, integrate, and refine raw data into meaningful insights.

Testing 52
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Available Now! Automated Testing for Data Transformations

Wayne Yaddow

Selecting the strategies and tools for validating data transformations and data conversions in your data pipelines. Introduction Data transformations and data conversions are crucial to ensure that raw data is organized, processed, and ready for useful analysis.

Testing 52
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Key Challenges Affecting Data Transformations—Dev and Testing

Wayne Yaddow

Common challenges and practical mitigation strategies for reliable data transformations. Photo by Mika Baumeister on Unsplash Introduction Data transformations are important processes in data engineering, enabling organizations to structure, enrich, and integrate data for analytics , reporting, and operational decision-making.

Testing 52
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Functional Gaps in Your Data Transformation Testing Tools?

Wayne Yaddow

Managing tests of complex data transformations when automated data testing tools lack important features? Photo by Marvin Meyer on Unsplash Introduction Data transformations are at the core of modern business intelligence, blending and converting disparate datasets into coherent, reliable outputs.

Testing 52
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Data transformation takes flight at Atlanta’s Hartsfield-Jackson airport

CIO Business Intelligence

As part of its plan, the IT team conducted a wide-ranging data assessment to determine who has access to what data, and each data source’s encryption needs. There are a lot of variables that determine what should go into the data lake and what will probably stay on premise,” Pruitt says.