Remove Data Governance Remove Data Lake Remove Metadata Remove Structured Data
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Data governance in the age of generative AI

AWS Big Data

Data is your generative AI differentiator, and a successful generative AI implementation depends on a robust data strategy incorporating a comprehensive data governance approach. Data governance is a critical building block across all these approaches, and we see two emerging areas of focus.

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How gaming companies can use Amazon Redshift Serverless to build scalable analytical applications faster and easier

AWS Big Data

A data hub is a center of data exchange that constitutes a hub of data repositories and is supported by data engineering, data governance, security, and monitoring services. A data hub contains data at multiple levels of granularity and is often not integrated.

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Why You Need a Data Catalog & How to Choose One

Octopai

If the point of Business Intelligence (BI) data governance is to leverage your datasets to support information transparency and decision-making, then it’s fair to say that the data catalog is key for your BI strategy. At least, as far as data analysis is concerned. The Benefits of Structured Data Catalogs.

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Data Swamp, Data Lake, Data Lakehouse: What to Know

Alation

Data Swamp vs Data Lake. When you imagine a lake, it’s likely an idyllic image of a tree-ringed body of reflective water amid singing birds and dabbling ducks. I’ll take the lake, thank you very much. Many organizations have built a data lake to solve their data storage, access, and utilization challenges.

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Why Spreadsheets Are Your Secret Weapon for Efficient Data Governance

Alation

Data governance is traditionally applied to structured data assets that are most often found in databases and information systems. This blog focuses on governing spreadsheets that contain data, information, and metadata, and must themselves be governed. Simply put, metadata adds context.

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Top Graph Use Cases and Enterprise Applications (with Real World Examples)

Ontotext

Specifically, the increasing amount of data being generated and collected, and the need to make sense of it, and its use in artificial intelligence and machine learning, which can benefit from the structured data and context provided by knowledge graphs. We get this question regularly. million users.

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In-depth with CDO Christopher Bannocks

Peter James Thomas

I have since run and driven transformation in Reference Data, Master Data , KYC [3] , Customer Data, Data Warehousing and more recently Data Lakes and Analytics , constantly building experience and capability in the Data Governance , Quality and data services domains, both inside banks, as a consultant and as a vendor.