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The Missing Link in Enterprise Data Governance: Metadata

Octopai

In order to figure out why the numbers in the two reports didn’t match, Steve needed to understand everything about the data that made up those reports – when the report was created, who created it, any changes made to it, which system it was created in, etc. Enterprise data governance. Metadata in data governance.

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Data governance in the age of generative AI

AWS Big Data

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. Data discoverability Unlike structured data, which is managed in well-defined rows and columns, unstructured data is stored as objects.

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What is data governance? Best practices for managing data assets

CIO Business Intelligence

The Business Application Research Center (BARC) warns that data governance is a highly complex, ongoing program, not a “big bang initiative,” and it runs the risk of participants losing trust and interest over time. The program must introduce and support standardization of enterprise data.

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From Data Silos to Data Fabric with Knowledge Graphs

Ontotext

Added to this is the increasing demands being made on our data from event-driven and real-time requirements, the rise of business-led use and understanding of data, and the move toward automation of data integration, data and service-level management. Knowledge Graphs are the Warp and Weft of a Data Fabric.

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How to Build Knowledge Graphs for Enterprise Applications with Two Industry Leaders

Ontotext

Knowledge graphs have greatly helped to successfully enhance business-critical enterprise applications, especially those where high performance tagging and agile data integration is needed. Enterprises generate an enormous amount of data and content every minute. How can you build knowledge graphs for enterprise applications?

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Throwing Your Data Into the Ocean

Ontotext

That means removing errors, filling in missing information and harmonizing the various data sources so that there is consistency. Once that is done, data can be transformed and enriched with metadata to facilitate analysis. Knowledge graphs help with data analysis in a number of ways.

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The Role of AI and ML in Model Governance

Alation

A data catalog is a central hub for XAI and understanding data and related models. While “operational exhaust” arrived primarily as structured data, today’s corpus of data can include so-called unstructured data. These methods and their results need to be captured, but how? Other Technologies. Conclusion.