Remove product data-catalog
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Manage concurrent write conflicts in Apache Iceberg on the AWS Glue Data Catalog

AWS Big Data

In modern data architectures, Apache Iceberg has emerged as a popular table format for data lakes, offering key features including ACID transactions and concurrent write support. Consider a common scenario: A streaming pipeline continuously writes data to an Iceberg table while scheduled maintenance jobs perform compaction operations.

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Expand data access through Apache Iceberg using Delta Lake UniForm on AWS

AWS Big Data

The landscape of big data management has been transformed by the rising popularity of open table formats such as Apache Iceberg, Apache Hudi, and Linux Foundation Delta Lake. These formats, designed to address the limitations of traditional data storage systems, have become essential in modern data architectures.

Metadata 122
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Announcing Open Source DataOps Data Quality TestGen 3.0

DataKitchen

Announcing DataOps Data Quality TestGen 3.0: Open-Source, Generative Data Quality Software. It assesses your data, deploys production testing, monitors progress, and helps you build a constituency within your company for lasting change. New Quality Dashboard & Score Explorer. DataOps just got more intelligent.

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Demystify data sharing and collaboration patterns on AWS: Choosing the right tool for the job

AWS Big Data

Data is the most significant asset of any organization. However, enterprises often encounter challenges with data silos, insufficient access controls, poor governance, and quality issues. Embracing data as a product is the key to address these challenges and foster a data-driven culture.

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How to Evaluate a Data Catalog

More data, more problems. Do you struggle to find, understand, and trust data in your daily work? A data catalog will make your work life easier -- and more productive. This guide offers handy tips for evaluating data catalogs. But where do you start?

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Streamline data discovery with precise technical identifier search in Amazon SageMaker Unified Studio

AWS Big Data

Were excited to introduce a new enhancement to the search experience in Amazon SageMaker Catalog , part of the next generation of Amazon SageMaker exact match search using technical identifiers. This yields results with exact precision, dramatically improving the speed and accuracy of data discovery.

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Streamline AI-driven analytics with governance: Integrating Tableau with Amazon DataZone

AWS Big Data

Amazon DataZone is a data management service that makes it faster and easier for customers to catalog, discover, share, and govern data stored across AWS, on premises, and from third-party sources. Use case Amazon DataZone addresses your data sharing challenges and optimizes data availability.

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Why Modern Data Challenges Require a New Approach to Governance

A healthy data-driven culture minimizes knowledge debt while maximizing analytics productivity. Agile Data Governance is the process of creating and improving data assets by iteratively capturing knowledge as data producers and consumers work together so that everyone can benefit.