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The Symbiotic Relationship Between Data Governance and AI

David Menninger's Analyst Perspectives

Data governance has always been a critical part of the data and analytics landscape. However, for many years, it was seen as a preventive function to limit access to data and ensure compliance with security and data privacy requirements. Data governance is integral to an overall data intelligence strategy.

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

erwin

What is Data Modeling? 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.

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5 Ways Data Modeling Is Critical to Data Governance

erwin

Enterprises are trying to manage data chaos. They also face increasing regulatory pressure because of global data regulations , such as the European Union’s General Data Protection Regulation (GDPR) and the new California Consumer Privacy Act (CCPA), that went into effect last week on Jan. GDPR: Key Differences.

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The future of data: A 5-pillar approach to modern data management

CIO Business Intelligence

In todays economy, as the saying goes, data is the new gold a valuable asset from a financial standpoint. A similar transformation has occurred with data. More than 20 years ago, data within organizations was like scattered rocks on early Earth.

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Data Governance 2.0: The CIO’s Guide to Collaborative Data Governance

erwin

In the data-driven era, CIO’s need a solid understanding of data governance 2.0 … Data governance (DG) is no longer about just compliance or relegated to the confines of IT. Today, data governance needs to be a ubiquitous part of your organization’s culture.

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7 types of tech debt that could cripple your business

CIO Business Intelligence

These areas are considerable issues, but what about data, security, culture, and addressing areas where past shortcuts are fast becoming todays liabilities? Types of data debt include dark data, duplicate records, and data that hasnt been integrated with master data sources.

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Specialized tools for machine learning development and model governance are becoming essential

O'Reilly on Data

A few years ago, we started publishing articles (see “Related resources” at the end of this post) on the challenges facing data teams as they start taking on more machine learning (ML) projects. So, why is this new open source project resonating with data scientists and machine learning engineers? Model governance.