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How Metadata Makes Data Meaningful

erwin

Metadata is an important part of data governance, and as a result, most nascent data governance programs are rife with project plans for assessing and documenting metadata. But in many scenarios, it seems that the underlying driver of metadata collection projects is that it’s just something you do for data governance.

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How Metadata Makes Data Meaningful

erwin

Metadata is an important part of data governance, and as a result, most nascent data governance programs are rife with project plans for assessing and documenting metadata. But in many scenarios, it seems that the underlying driver of metadata collection projects is that it’s just something you do for data governance.

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As insurers look to be more agile, data mesh strategies take centerstage

CIO Business Intelligence

This is where data fabric tools with their focus on orchestration, contextual layering, and metadata management are important elements to add to the equation. Data fabric introduces an intelligent semantic layer that orchestrates disparate data sources, applications, and services into a unified and easily accessible framework.

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What’s the Current State of Data Governance and Automation?

erwin

Digital transformation and data standards/uniformity round out the top five data governance drivers, with 37 and 36 percent, respectively. Constructing a Digital Transformation Strategy: How Data Drives Digital. And close to 50 percent have deployed data catalogs and business glossaries.

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Doing Cloud Migration and Data Governance Right the First Time

erwin

No less daunting, your next step is to re-point or even re-platform your data movement processes. And you can’t risk false starts or delayed ROI that reduces the confidence of the business and taint this transformational initiative. More and more companies are looking at cloud migration.

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What Is Data Modeling? Data Modeling Best Practices for Data-Driven Organizations

erwin

Data modeling is a process that enables organizations to discover, design, visualize, standardize and deploy high-quality data assets through an intuitive, graphical interface. Data models provide visualization, create additional metadata and standardize data design across the enterprise. SQL or NoSQL?

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Data Cleansing and Business Efficiency

Octopai

A Strategic Approach to Data Cleansing With Octopai’s automated data lineage, data cleansing transcends its traditional role, becoming a strategic endeavor that drives efficiency, ensures data integrity, and unlocks business insights.