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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 Race For Data Quality in a Medallion Architecture

DataKitchen

By incorporating automated alerting systems, regular QA checks, and well-defined SLAs for data loading, data engineering teams can better manage Day 2 production challenges, helping to preserve the integrity and reliability of their analytical outputs.

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Data Observability and Data Quality Testing Certification Series

DataKitchen

Data Observability and Data Quality Testing Certification Series We are excited to invite you to a free four-part webinar series that will elevate your understanding and skills in Data Observation and Data Quality Testing.

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DataOps: Managing the Process and Technology

David Menninger's Analyst Perspectives

For decades, data integration was a rigid process. Data was processed in batches once a month, once a week or once a day. Organizations needed to make sure those processes were completed successfully—and reliably—so they had the data necessary to make informed business decisions.

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Beginner’s Guide to Machine Learning Testing With DeepChecks

KDnuggets

Perform data integrity tests and generate model evaluation reports by writing a few lines of code.

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How to manage data integration during an acquisition

CIO Business Intelligence

Organizations need effective data integration and to embrace a hybrid IT environment that allows them to quickly access and leverage all their data—whether stored on mainframes or in the cloud. How does a company approach data integration and management when in the throes of an M&A?

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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.

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