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Data governance in the age of generative AI

AWS Big Data

Data governance is a critical building block across all these approaches, and we see two emerging areas of focus. First, many LLM use cases rely on enterprise knowledge that needs to be drawn from unstructured data such as documents, transcripts, and images, in addition to structured data from data warehouses.

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Cloudera Named a Visionary in the Gartner MQ for Cloud DBMS

Cloudera

We scored the highest in hybrid, intercloud, and multi-cloud capabilities because we are the only vendor in the market with a true hybrid data platform that can run on any cloud including private cloud to deliver a seamless, unified experience for all data, wherever it lies.

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Building a Beautiful Data Lakehouse

CIO Business Intelligence

But the data repository options that have been around for a while tend to fall short in their ability to serve as the foundation for big data analytics powered by AI. Traditional data warehouses, for example, support datasets from multiple sources but require a consistent data structure. Meet the data lakehouse.

Data Lake 107
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Do I Need a Data Catalog?

erwin

Given the value this sort of data-driven insight can provide, the reason organizations need a data catalog should become clearer. It’s no surprise that most organizations’ data is often fragmented and siloed across numerous sources (e.g., Three Types of Metadata in a Data Catalog. Technical Metadata.

Metadata 132
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A hybrid approach in healthcare data warehousing with Amazon Redshift

AWS Big Data

Data warehouses play a vital role in healthcare decision-making and serve as a repository of historical data. A healthcare data warehouse can be a single source of truth for clinical quality control systems. What is a dimensional data model? What is a dimensional data model?

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Why Spreadsheets Are Your Secret Weapon for Efficient Data Governance

Alation

Other forms of governance address specific sets or domains of data including information governance (for unstructured data), metadata governance (for data documentation), and domain-specific data (master, customer, product, etc.). Data catalogs and spreadsheets are related in many ways.

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Five benefits of a data catalog

IBM Big Data Hub

For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance. It uses metadata and data management tools to organize all data assets within your organization. Technical metadata to describe schemas, indexes and other database objects.