In this episode of the Databricks Diaries, Daniel is joined by James Blagg, a seasoned Chief Data Officer with over 25 years of experience leading data strategy, architecture, and modernisation programmes across financial services.

James shares hard-won lessons from a career that spans the 2008 financial crisis, the big data hype cycle, the move from Teradata appliances to cloud-native platforms, and now the AI wave. It's a candid conversation about what actually drives value in data — and the gap between vendor promises and operational reality.

What's covered:

• James's career journey from Oracle PL/SQL developer to CDO
• Leading BI teams at Lloyds through the financial crisis and the HBOS integration
• Nationwide's data simplification programme and the "almost cloud" Teradata investment
• How platform evaluation has changed — and why cost, skills, and relationships now matter more than features
• Why "it's on the roadmap" is the most dangerous phrase in vendor selection
• The MVP hypothesis approach to picking analytics use cases
• Why so many data warehouse projects are perceived as failures (and why metadata investment is finally fixing it)
• Where AI really sits on the maturity curve — and why financial services is 10–15 years away from full back-office adoption
• A practical playbook for governance, cost monitoring, and security guardrails before scaling AI on Databricks
• The truth about cloud consumption pricing and reserved pricing deals

In this episode of The Databricks Diaries, Andy Davis is joined by Claire Thompson, Chief Data Officer at Quilter, to explore what AI readiness really looks like inside a modern financial services organisation.

Claire shares her perspective on the pace of change in data and AI, why strong foundations still matter, and why organisations cannot afford to wait for everything to be perfect before starting. The conversation covers how to build momentum through practical use cases, engage senior stakeholders, create safe environments for experimentation, and make governance a helpful enabler rather than a blocker.

Andy and Claire also discuss the importance of continuous learning within data teams, how to prioritise AI opportunities, and why technical teams need to get better at telling the story of the value they create.

This episode is for data, technology and business leaders who want a grounded view of AI adoption beyond the hype, with practical lessons on moving from early experimentation to scalable, valuable outcomes.

In this episode of the Databricks Diaries, host Andy is joined by Gordon Logan, Director of Data Services at PRS for Music, for a deep dive into the unique challenges of preparing a century-old organisation for the AI era. Managing data for over 180,000 members—including composers, songwriters, and publishers—Gordon shares how his team navigates astronomical data volumes driven by the modern shift to streaming and digital consumption. He discusses the critical transition from isolated experiments to a structured, momentum-driven AI strategy backed by executive leadership.

Gordon explores the essential components of building an AI-ready culture, prioritising data literacy and "AI efficacy" to ensure the workforce uses powerful tools like Copilot ethically and responsibly. The conversation highlights a disciplined, business-led approach to use cases, moving away from "technology vanity exercises" and focusing instead on measurable outcomes like accurate royalty distribution and improved member services. Listeners will learn how PRS for Music employs a cross-functional AI team to stress-test hypotheses, ensuring that every technological advancement facilitates tangible business value while protecting the sensitive data of the UK’s creative community.