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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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Oracle Wants to Be the Database for AI

David Menninger's Analyst Perspectives

Oracle recently hosted its annual Database Analyst Summit, sharing the vision and strategy for its data platform. While much of the event was under non-disclosure as product plans and launch schedules are finalized, it still served as a useful recap of the broad portfolio of data platform capabilities that Oracle has to offer.

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Data Integrity, the Basis for Reliable Insights

Sisense

We live in a world of data: There’s more of it than ever before, in a ceaselessly expanding array of forms and locations. Dealing with Data is your window into the ways data teams are tackling the challenges of this new world to help their companies and their customers thrive. What is data integrity?

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The DataOps Vendor Landscape, 2021

DataKitchen

DataOps needs a directed graph-based workflow that contains all the data access, integration, model and visualization steps in the data analytic production process. It orchestrates complex pipelines, toolchains, and tests across teams, locations, and data centers. Meta-Orchestration .

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Scaling RISE with SAP data and AWS Glue

AWS Big Data

The SAP OData connector supports both on-premises and cloud-hosted (native and SAP RISE) deployments. By using the AWS Glue OData connector for SAP, you can work seamlessly with your data on AWS Glue and Apache Spark in a distributed fashion for efficient processing. On your Visual Editor canvas, select your SAP sources.

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Artificial intelligence and machine learning adoption in European enterprise

O'Reilly on Data

Given the end-to-end nature of many data products and applications, sustaining ML and AI requires a host of tools and processes, ranging from collecting, cleaning, and harmonizing data, understanding what data is available and who has access to it, being able to trace changes made to data as it travels across a pipeline, and many other components.

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Private cloud makes its comeback, thanks to AI

CIO Business Intelligence

Private cloud providers may be among the key beneficiaries of today’s generative AI gold rush as, once seemingly passé in favor of public cloud, CIOs are giving private clouds — either on-premises or hosted by a partner — a second look. The Milford, Conn.-based We’re keeping that tight control and keeping it in the private cloud.”

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