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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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You Cannot Get to the Moon on a Bike!

Ontotext

And each of these gains requires data integration across business lines and divisions. Limiting growth by (data integration) complexity Most operational IT systems in an enterprise have been developed to serve a single business function and they use the simplest possible model for this. We call this the Bad Data Tax.

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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. Data-related decisions, processes, and controls subject to data governance must be auditable.

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AI-powered Solutions to Personalized Healthcare Using Knowledge Graphs: An Interview with Remzi Celebi

Ontotext

In order to create an interoperable health data record, we should be able to integrate personal health data (which comes in various formats and structures and varying quality) into a shareable format with other systems and individuals. We are planning to develop or use AI-based tools for each of these problems.

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Automated PowerPoint Generation, or Making a “Slide Factory”

Juice Analytics

These options offer more powerful capabilities but may not come with the traditional joys of a PowerPoint document (five solutions below). Finally, if you are a developer, there are a couple technical solutions that allow you to construction the data integration workflows you need. Try Juicebox -- It's Free!

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The Data Journey: From Raw Data to Insights

Sisense

In all cases the data will eventually be loaded into a different place, so it can be managed, and organized, using a package such as Sisense for Cloud Data Teams. Using data pipelines and data integration between data storage tools, engineers perform ETL (Extract, transform and load).

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The Role of AI and ML in Model Governance

Alation

Data management is not yet a solved problem, but modern data management is leagues ahead of prior approaches. These include tracking, documenting, monitoring, versioning, and controlling access to AI/ML models. A data catalog is a central hub for XAI and understanding data and related models. Other Technologies.