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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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What is data analytics? Analyzing and managing data for decisions

CIO Business Intelligence

What is data analytics? Data analytics is a discipline focused on extracting insights from data. It comprises the processes, tools and techniques of data analysis and management, including the collection, organization, and storage of data. What are the four types of data analytics?

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Author visual ETL flows on Amazon SageMaker Unified Studio (preview)

AWS Big Data

From the Unified Studio, you can collaborate and build faster using familiar AWS tools for model development, generative AI, data processing, and SQL analytics. You can use a simple visual interface to compose flows that move and transform data and run them on serverless compute.

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Fire Your Super-Smart Data Consultants with DataOps

DataKitchen

The sales team at the consulting firm proposed that a bigger budget was needed to keep the data factory churning out enterprise-critical analytics. The data requirements of a thriving business are never complete. DataOps improves the robustness, transparency and efficiency of data workflows through automation.

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Accelerate analytics and AI innovation with the next generation of Amazon SageMaker

AWS Big Data

At AWS re:Invent 2024, we announced the next generation of Amazon SageMaker , the center for all your data, analytics, and AI. The final model provides sales teams with the highest-value opportunities, which they can visualize in a business intelligence dashboard and take action on immediately.

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Data Observability and Monitoring with DataOps

DataKitchen

That’s a fair point, and it places emphasis on what is most important – what best practices should data teams employ to apply observability to data analytics. We see data observability as a component of DataOps. In our definition of data observability, we put the focus on the important goal of eliminating data errors.

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Announcing zero-ETL integrations with AWS Databases and Amazon Redshift

AWS Big Data

As customers become more data driven and use data as a source of competitive advantage, they want to easily run analytics on their data to better understand their core business drivers to grow sales, reduce costs, and optimize their businesses.