From Projects to Products: Why Data Products Are Still Hard

From Projects to Products: Why Data Products Are Still Hard
A Data Products Book Launch & Practitioner Panel

About the event

This meetup marks the release of Amy Raygada’s new book on Data Products and explores why, despite years of discussion, data products are still hard to implement in practice.
Data products are not a new concept. For years, organisations have talked about treating data as a product — with clear ownership, well-defined interfaces, and measurable business value. And yet, many teams continue to struggle with fragmented dashboards, inconsistent metrics, and slow, reactive delivery.
So why is this still so difficult?

In this meetup, we’ll unpack why data products remain hard in practice — not because teams lack tools or frameworks, but because meaning, ownership, and operating models are often misunderstood or only partially implemented.
Through in-depth practitioner talks and discussion, we’ll explore:

• Why data initiatives often slip back into project mode
• Where ownership breaks down across domains and platforms
• How weak semantics and unclear definitions erode trust
• What changes when data products are treated as long-lived products rather than delivery artefacts
• Why AI and advanced analytics amplify these challenges instead of solving them

The conversation is grounded in real delivery experience across engineering, architecture, and data strategy. It also features insights from Amy Raygada’s newly released book, which captures lessons learned from years of hands-on work helping organisations move from intent to execution.
Expect practical perspectives, honest trade-offs, and an open discussion — not hype, not vendor pitches, and no one-size-fits-all answers.

About the speakers

Amy Raygada
Principal Data & AI Strategist at Thoughtworks | Author
Amy Raygada is a Principal Data & AI Strategist at Thoughtworks, with over a decade of experience helping organisations design and govern data products that deliver real business impact. Her work spans data product strategy, governance, operating models, and AI readiness, with a strong focus on aligning technical capabilities with decision-making.

This meetup marks the release of her new book on Data Products, bringing together lessons from years of real-world delivery across industries.

Kiran Prakash
Director, Data & AI at Thoughtworks
Kiran Prakash is a Director in the Data & AI service line at Thoughtworks, working with organisations to design and scale data-driven systems. In his talk “What We Talk About When We Talk About Data Products,” Kiran presents a practical approach to designing, implementing, and governing data products. Drawing on real-world experience, he clarifies what data products are — and what they are not — and explores how teams can work backwards from use cases, apply adaptable implementation patterns, and use governance mechanisms such as fitness functions to keep data products aligned over time.

Carsten Fritsch
Principal Data Engineer at Thoughtworks
Carsten Fritsch is a Principal Data Engineer at Thoughtworks in Berlin, with deep experience in data engineering, analytics architecture, and data modelling at scale. His work focuses on semantic layers, shared metrics, and the practical challenges of operationalising meaning across organisations. Carsten brings a grounded perspective on why semantics are foundational to trustworthy data products — especially as organisations move toward AI-driven use cases.

Format

• Each speaker will deliver a 25–30 minute talk, followed by Q&A
• Final panel discussion with all speakers
• Open audience Q&A
• Informal networking and book signing

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Code of Conduct
We adhere to the Berlin Code of Conduct to ensure a welcoming and respectful environment for all participants. The event space operates under largely compatible Thoughtworks Meetups & Events CoC.

Accessibility
The Location is accessible for wheelchair users. This includes the entrance (no steps to get into the location), toilets and the stage.