Data Citizens Dialogues

The secret to elevating data governance and AI success? It's all about mindset. Gaurav Patole, Principal Data Strategist, Data & AI Governance Specialist at ThoughtWorks, reveals how the principles of physics can revolutionize how organizations handle data quality. In a world flooded with unstructured chaos—PDFs, videos, emails—how do you ensure AI models trust what they see? Gaurav’s innovative 'Newton's laws' for data quality offer a surprisingly simple, yet profoundly powerful framework to align technical practices with business value. You'll discover:
Why pushing technical jargon in business conversations causes resistance—and how to flip that dynamic
The real meaning of a data product: the smallest unit of business impact and how to identify it
How organizations tend to fragment data governance—and what steps can unify data at scale
The evolving role of data marketplaces and AI in simplifying access, ownership and quality controls
Insights from a decade of data mesh experience, including the culture shift needed to make data as a product a reality
You can find Gaurav's book at https://www.thoughtworks.com/en-us/insights/books/data-quality-roi and check out more episodes at Collibra.com/podcasts

Transform your data governance approach by treating it as a brand, not just a policy.
In this episode, Adam Coladipietro and Serena Cromarty from British Columbia Lottery Corporation reveal how they shifted their data culture from mandates to motivation through innovative branding, storytelling and user-focused design. Discover how they turned a 281-page strategy deck into an engaging 18-slide interactive experience, winning internal attention. Learn why hiring for curiosity and communication over just technical skill creates a collaborative, empowered data community.
If your organization struggles to make data initiatives stick, this episode offers concrete tactics to make it compelling, approachable, and human-centered. Perfect for leaders craving practical strategies to embed data culture deeply into their organization, without the usual noise and resistance. Step beyond traditional compliance and see how brand-building and empathy can unlock your data team's potential.

Most organizations are still managing data as a collection of tables and reports, but the future demands a shift to truly business-owned data products. Brandon Dombroski, Managing Director, Head of Data Quality and Data Platform Business Ownership at MUFG, reveals how transforming data ownership and engagement unlocks rapid scalability and reduces costs - like cutting data quality rule expenses by 99% - and positions data as a strategic asset rather than just a technical commodity.
In this episode, you’ll discover how MUFG re-engaged the business in data governance, made data catalogs more accessible to non-technical users, and shifted from a data-infrastructure focus to delivering value-driven data products that genuinely serve business needs. Brandon shares a practical framework for evolving from traditional data lakes to a product-centric approach, emphasizing business ownership, use case alignment, and scalable data quality automation.
We also break down the importance of operationalizing data as a product rather than a table, how to foster business buy-in from top-down and bottoms-up strategies, and the emerging role of the Chief AI Officer as data and AI increasingly converge.

For too long, data governance has been framed as a constraint as opposed to the competitive advantage it ought to be. Which is exactly why Federico Frumento, Senior Data Governance Manager at Vodafone, makes the case for governance as a business enabler—one that helps organizations move faster, make better decisions and achieve real commercial outcomes.

By reframing governance around commercial outcomes in an era of generative AI, organizations can create a powerful “carrot” for investment—one that makes the connection between data quality and trustworthy AI impossible to ignore. Because, in the end, lasting impact comes from treating data governance as a collaborative discipline, where flexible frameworks adapt to real business needs and bridge business and technical teams to drive meaningful, cultural change.

Three reasons you should listen to this episode:

1. Data governance as a growth lever, not a roadblock. How reframing governance around business outcomes changes adoption, momentum and impact.

2. GenAI is the new catalyst for governance investment. Why the demand for trustworthy AI makes data quality—and governance—impossible to ignore.

3. What cultural change in data governance actually looks like. Flexible frameworks, collaboration and trust are essential to making governance stick across the business.

Resources
Connect with Thomas
Connect with Fede

Enjoyed this episode?
Be sure to follow us so you never miss an update. You can leave us a review on Apple or Spotify, and share it with your friends and colleagues to help others learn more about the importance of a data-first digital transformation approach.
Have questions? You can connect with us on LinkedIn. For more updates, please visit our website.

What does it really take to turn fragmented data into something teams can trust and use at scale? For Cirium’s Head of Data Governance, Candice Parfitt, it starts with tackling data silos head-on—using governance as the foundation for unifying data after years of growth through acquisition.

Recorded live at Data Citizens on the Road in London, Candice joins Thomas Brence to unpack what “good governance” actually demands from an organization. For governance to work in the real world, it should be seen as a shared discipline—one grounded in fit-for-purpose data, reinforced through continuous education and intentionally embedded in everyday work.

And as adoption grows, governance must be built in—not bolted on—so access, accountability and trust can scale together.

Three reasons you should listen to this episode:

1. Start where governance actually matters: Learn why getting foundational data fit for purpose is the fastest way to unlock better products, clearer analysis and stronger trust.

2. Make data literacy stick: See how continuous, real-world education—using your own data and use cases—builds alignment across teams without slowing work down.

3. Move toward governance by design: Understand when and how to shift from open access to intentional controls by capturing metadata early and logging real use cases.

Resources
Connect with Thomas
Connect with Candice

Enjoyed this episode?
Be sure to follow us so you never miss an update. You can leave us a review on Apple or Spotify, and share it with your friends and colleagues to help others learn more about the importance of a data-first digital transformation approach.
Have questions? You can connect with us on LinkedIn. For more updates, please visit our website.