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Best Practices for Metadata Management

Alation

What Is Metadata? Metadata is information about data. A clothing catalog or dictionary are both examples of metadata repositories. Indeed, a popular online catalog, like Amazon, offers rich metadata around products to guide shoppers: ratings, reviews, and product details are all examples of metadata.

Metadata 105
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Metadata is Like Packaging: Seeing Beyond the Library Card Metaphor

Ontotext

way we package information has a lot to do with metadata. The somewhat conventional metaphor about metadata is the one of the library card. This metaphor has it that books are the data and library cards are the metadata helping us find what we need, want to know more about or even what we don’t know we were looking for.

Metadata 124
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Documenting and Managing Governance, Risk and Compliance with Business Process

erwin

Shockingly, a lot of organizations, even today, manage this through, either homemade tools or documents, checklists, Excel files, custom-made databases and so on and so forth. Traditionally, these are manually documented, monitored and managed. Processes produce, process and consume data –information captured in the metadata layer.

Risk 98
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Driving the Next Wave of Data Lineage Visualization with Automation

Octopai

The result was a spider web of connections and relationships that were difficult to manage, characterize, document, and maintain. Simply put, data lineage is a tracking tool that documents the journey from data source to target. This visual aspect is the key to the usefulness of any large and complex data landscape.

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What is a data architect? Skills, salaries, and how to become a data framework master

CIO Business Intelligence

The data architect is responsible for visualizing and designing an organization’s enterprise data management framework. Data architects and data engineers work together to visualize and build the enterprise data management framework. In some ways, the data architect is an advanced data engineer.

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What is data governance? Best practices for managing data assets

CIO Business Intelligence

They must be accompanied by documentation to support compliance-based and operational auditing requirements. Programs must support proactive and reactive change management activities for reference data values and the structure/use of master data and metadata. The program must introduce and support standardization of enterprise data.

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Data governance in the age of generative AI

AWS Big Data

The need for an end-to-end strategy for data management and data governance at every step of the journey—from ingesting, storing, and querying data to analyzing, visualizing, and running artificial intelligence (AI) and machine learning (ML) models—continues to be of paramount importance for enterprises.