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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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The DataOps Vendor Landscape, 2021

DataKitchen

Testing and Data Observability. We have also included vendors for the specific use cases of ModelOps, MLOps, DataGovOps and DataSecOps which apply DataOps principles to machine learning, AI, data governance, and data security operations. . Genie — Distributed big data orchestration service by Netflix.

Testing 300
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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.

Data Lake 130
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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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Introducing a new unified data connection experience with Amazon SageMaker Lakehouse unified data connectivity

AWS Big Data

For each service, you need to learn the supported authorization and authentication methods, data access APIs, and framework to onboard and test data sources. This approach simplifies your data journey and helps you meet your security requirements. On your project, in the navigation pane, choose Data. Choose Next.

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End-to-end development lifecycle for data engineers to build a data integration pipeline using AWS Glue

AWS Big Data

Many AWS customers have integrated their data across multiple data sources using AWS Glue , a serverless data integration service, in order to make data-driven business decisions. Are there recommended approaches to provisioning components for data integration?

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Why you should care about debugging machine learning models

O'Reilly on Data

In addition to newer innovations, the practice borrows from model risk management, traditional model diagnostics, and software testing. Security vulnerabilities : adversarial actors can compromise the confidentiality, integrity, or availability of an ML model or the data associated with the model, creating a host of undesirable outcomes.