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AWS Glue for Handling Metadata

Analytics Vidhya

The post AWS Glue for Handling Metadata appeared first on Analytics Vidhya. The managed service offers a simple and cost-effective method of categorizing and managing big data in an enterprise. It provides organizations with […].

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Enterprises can gain an edge with Metadata Management

CIO Business Intelligence

Central to this is metadata management, a critical component for driving future success AI and ML need large amounts of accurate data for companies to get the most out of the technology. Let’s dive into what that looks like, what workarounds some IT teams use today, and why metadata management is the key to success.

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Enhance data governance with enforced metadata rules in Amazon DataZone

AWS Big Data

We’re excited to announce a new feature in Amazon DataZone that offers enhanced metadata governance for your subscription approval process. With this update, domain owners can define and enforce metadata requirements for data consumers when they request access to data assets. Key benefits The feature benefits multiple stakeholders.

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Enrich your AWS Glue Data Catalog with generative AI metadata using Amazon Bedrock

AWS Big Data

Metadata can play a very important role in using data assets to make data driven decisions. Generating metadata for your data assets is often a time-consuming and manual task. This post shows you how to enrich your AWS Glue Data Catalog with dynamic metadata using foundation models (FMs) on Amazon Bedrock and your data documentation.

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Why Modern Data Challenges Require a New Approach to Governance

By capturing metadata and documentation in the flow of normal work, the data.world Data Catalog fuels reproducibility and reuse, enabling inclusivity, crowdsourcing, exploration, access, iterative workflow, and peer review. It adapts the deeply proven best practices of Agile and Open software development to data and analytics.

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Neptune.ai?—?A Metadata Store for MLOps

Analytics Vidhya

A centralized location for research and production teams to govern models and experiments by storing metadata throughout the ML model lifecycle. A Metadata Store for MLOps appeared first on Analytics Vidhya. Keeping track of […]. The post Neptune.ai?—?A

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Octopai Acquisition Enhances Metadata Management to Trust Data Across Entire Data Estate

Cloudera

It leverages knowledge graphs to keep track of all the data sources and data flows, using AI to fill the gaps so you have the most comprehensive metadata management solution. Together, Cloudera and Octopai will help reinvent how customers manage their metadata and track lineage across all their data sources.

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How to Operationalize Data From Multiple Sources to Deliver Actionable Insights

Speaker: Speakers from SafeGraph, Facteus, AWS Data Exchange, SimilarWeb, and AtScale

Leveraging metadata (labels, annotations) for deep dimensional analysis. In this webinar, you will learn about: Blending various high quality third-party datasets with internal data. Extending analysis-ready data to all of your business stakeholders at scale.