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# Understanding Data Governance: Myths and Insights

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Chapter 1: Introduction to Data Governance

Welcome to your weekly roundup of insights on data, AI, and analytics! In this blog, we curate the most significant data-related stories of the week, highlighting what's trending and what's not. If you’re pressed for time, you can catch our weekly vlog or listen to our podcast for a quick update.

As a bonus, there's a downloadable slide deck at the end of this post filled with valuable resources and links, available for free—feel free to share it with your network!

Now, let's delve into the top five data stories of the week!

Section 1.1: What is Data Governance?

According to leaders at BCG, "For many organizations, data governance is akin to flossing. They recognize its importance but often prefer to engage in other activities." The reality is that data governance remains a significant challenge: 60% of survey respondents rate their data governance capabilities as lacking. Furthermore, a report by Gartner reveals that 42% of data and analytics leaders do not evaluate or monitor their governance practices.

This section will differentiate data governance from data management, explore ten critical areas of data management that support data governance, and outline the goals and advantages of implementing effective data governance strategies. Read more about it here.

Description: This concise video provides a clear explanation of data governance, outlining its significance and fundamental concepts.

Section 1.2: Debunking Myths About Decision Making

A compelling article by Cheryl Strauss Einhorn in the Harvard Business Review discusses 11 common misconceptions regarding decision-making. Some notable myths include:

  • "I know I'm correct; I merely seek data or opinions that support my viewpoint."
  • "Decision-making is a straightforward, linear process."
  • "I possess all the information necessary."
  • "There’s only one way to approach this."

For a deeper understanding, click here.

Section 1.3: The Evolution of Data as Software

Five years back, software systems were primarily defined by the code written. Today, however, the focus has shifted to the data that powers these systems. As AI continues to take over some traditional programming tasks, developers are increasingly prioritizing data alongside source code. The emergence of comprehensive data infrastructures and development tools parallels that of software development, promising to revolutionize software creation.

Thanks to Adam for sharing this insightful piece! Learn more here.

Chapter 2: AI and Digital Transformation

AI is not merely about technical skills; it’s fundamentally about mindset. Amit Shah, President of 1–800-FLOWERS.COM, INC., shares valuable insights on the MIT Sloan Management Review's "Me, Myself, and AI" podcast, emphasizing the importance of adapting to a rapidly changing environment and utilizing data to enhance customer experiences. Find out more here.

Description: This video explores the concept of data governance in detail, providing a foundational understanding for viewers.

Chapter 3: Celebrating Data Leaders

Kudos to the CDO Magazine for announcing its 2021 list of Global Data Power Women. Additionally, don’t forget to register for the upcoming CDO and Data Leaders Global Summit on May 5th.

Furthermore, the remarkable journey of ShareChat deserves a mention. With an impressive user base of 60 million and 70TB of data, they successfully migrated to Google Cloud in just five hours without any data loss. This achievement showcases their innovative approach to data management.

Finally, a shoutout to Mathieu Cochelin of La Provence for his inspiring digital transformation narrative. For those looking for a fun work environment, my friend Dan Sandlin is hiring—apply now!

For more insights, check out our detailed slide deck with references.

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