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Getting started with AWS Glue Data Quality from the AWS Glue Data Catalog

AWS Big Data

AWS Glue is a serverless data integration service that makes it simple to discover, prepare, and combine data for analytics, machine learning (ML), and application development. Hundreds of thousands of customers use data lakes for analytics and ML to make data-driven business decisions.

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Data governance in the age of generative AI

AWS Big Data

Working with large language models (LLMs) for enterprise use cases requires the implementation of quality and privacy considerations to drive responsible AI. However, enterprise data generated from siloed sources combined with the lack of a data integration strategy creates challenges for provisioning the data for generative AI applications.

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Avoid generative AI malaise to innovate and build business value

CIO Business Intelligence

Capturing the “as-is” state of your environment, you’ll develop topology diagrams and document information on your technical systems. GenAI requires high-quality data. Ensure that data is cleansed, consistent, and centrally stored, ideally in a data lake. Assess your readiness.

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How Tricentis unlocks insights across the software development lifecycle at speed and scale using Amazon Redshift

AWS Big Data

Additionally, the scale is significant because the multi-tenant data sources provide a continuous stream of testing activity, and our users require quick data refreshes as well as historical context for up to a decade due to compliance and regulatory demands. Finally, data integrity is of paramount importance.

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What is Data Mapping?

Jet Global

Data mapping is essential for integration, migration, and transformation of different data sets; it allows you to improve your data quality by preventing duplications and redundancies in your data fields. The first step of data mapping is defining the scope of your data mapping project.

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Constructing A Digital Transformation Strategy: Putting the Data in Digital Transformation

erwin

Outsourcing these data management efforts to professional services firms only delays schedules and increases costs. With automation, data quality is systemically assured. The data pipeline is seamlessly governed and operationalized to the benefit of all stakeholders. Digital Transformation Strategy: Smarter Data.

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How data stores and governance impact your AI initiatives

IBM Big Data Hub

To optimize data analytics and AI workloads, organizations need a data store built on an open data lakehouse architecture. This type of architecture combines the performance and usability of a data warehouse with the flexibility and scalability of a data lake.