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Data Governance Maturity and Tracking Progress

erwin

Data governance is best defined as the strategic, ongoing and collaborative processes involved in managing data’s access, availability, usability, quality and security in line with established internal policies and relevant data regulations. Data Governance Is Business Transformation. Predictability.

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The Key Role of the Data Governance Partner

TDAN

A question was raised in a recent webinar about the role of the Data Architect and Data Modelers in a Data Governance program. My webinar with Dataversity was focused on Data Governance Roles as the Backbone of Your Program.

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A Survey Into Data Governance Tools

DataCamp

In a recent webinar, we discussed how data governance is a key component of an organization’s data strategy and enables it to harness the full value of data. For a data governance plan to succeed, it is important that the right tools and technology are employed.

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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. As Mr. Pörschmann highlighted at the beginning of the series, data governance works best when it is strongly aligned with the drivers, motivations and goals of the business.

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LLMOps for Your Data: Best Practices to Ensure Safety, Quality, and Cost

Speaker: Shreya Rajpal, Co-Founder and CEO at Guardrails AI & Travis Addair, Co-Founder and CTO at Predibase

However, productionizing LLMs comes with a unique set of challenges such as model brittleness, total cost of ownership, data governance and privacy, and the need for consistent, accurate outputs. Large Language Models (LLMs) such as ChatGPT offer unprecedented potential for complex enterprise applications.

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5 Data Governance Mistakes to Avoid

Alation

That means if you haven’t already incorporated a plan for data governance into your long-term vision for your business, the time is now. Let’s take a closer look at what data governance is — and the top five mistakes to avoid when implementing it. 5 common data governance mistakes 1.

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Data Governance and Metadata Management: You Can’t Have One Without the Other

erwin

When an organization’s data governance and metadata management programs work in harmony, then everything is easier. Data governance is a complex but critical practice. Data Governance Attitudes Are Shifting. Data Governance Attitudes Are Shifting.

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Partner Webinar: A Framework for Building Data Mesh Architecture

Speaker: Jeremiah Morrow, Nicolò Bidotti, and Achille Barbieri

Data teams in large enterprise organizations are facing greater demand for data to satisfy a wide range of analytic use cases. Yet they are continually challenged with providing access to all of their data across business units, regions, and cloud environments.

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How to Foster Data Culture (with Data Intelligence Technology!)

Speaker: Aaron Kalb, Co-Founder and CDAO at Alation

Throughout history, however, technology has sparked cultural change, and today, data intelligence technology, like data catalog software, is helping enterprises develop data cultures. Watch this webinar to learn: The surprising role of technology in shaping culture.

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How to Foster Data Culture (with Data Intelligence Technology!)

Speaker: Aaron Kalb, Co-Founder and CDAO at Alation

Throughout history, however, technology has sparked cultural change, and today, data intelligence technology, like data catalog software, is helping enterprises develop data cultures. Watch this webinar to learn: The surprising role of technology in shaping culture. How to leverage a data catalog to create a data culture.