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The Value of Data Governance and How to Quantify It

erwin

erwin recently hosted the second in its six-part webinar series on the practice of data governance and how to proactively deal with its complexities. Led by Frank Pörschmann of iDIGMA GmbH, an IT industry veteran and data governance strategist, the second webinar focused on “ The Value of Data Governance & How to Quantify It.”.

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Why Data Governance Is Crucial for All Enterprise-Level Businesses

Cloudera

Whether the enterprise uses dozens or hundreds of data sources for multi-function analytics, all organizations can run into data governance issues. Bad data governance practices lead to data breaches, lawsuits, and regulatory fines — and no enterprise is immune. . Everyone Fails Data Governance.

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Digital transformation 2025: What’s in, what’s out

CIO Business Intelligence

In 2025, businesses intentional with upskilling will maximize AI benefits with a competitive edge, while those who rush to incorporate AIs next big thing before their team is ready will be hindered in their efforts to innovate.

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The Never-Ending Evolution of Data Governance

erwin

At the root of data intelligence is data governance , which helps ensure the right level of data access, availability and usage based on a defined set of data policies and principles. The Importance of Data Governance. Organizations recognize the importance of effective data governance.

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How resilient CIOs future-proof to mitigate risks

CIO Business Intelligence

By implementing DPSM, organizations can focus on their data priorities, knowing where all their data lives and how to secure it, he says. This can assist CIOs in tackling data governance issues , he adds. Perez highlights metrics like reduced security incidents, compliance adherence, and improvements in data governance.

Risk 105
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Types of Data Models: Conceptual, Logical & Physical

erwin

While it may be feasible to have working sessions with stakeholders to review a logical and/or physical data model, it’s not always possible to scale these workshops to everyone within the organization. In any data governance endeavour, it’s a best practice to prioritize business-critical data elements and relate them to key business drivers.

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CIO Ryan Snyder on the benefits of interpreting data as a layer cake

CIO Business Intelligence

So Thermo Fisher Scientific CIO Ryan Snyder and his colleagues have built a data layer cake based on a cascading series of discussions that allow IT and business partners to act as one team. Martha Heller: What are the business drivers behind the data architecture ecosystem you’re building at Thermo Fisher Scientific?