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September 9 & 10 2026

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Interview: "We are moving from data-driven to value-driven"

Joep Steenbeek | Head of Data Office | City of Amsterdam

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Jessica Ruland | Lead Product Manager | TicketSwap

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September 9 & 10 2025 | Jaarbeurs Utrecht Free ticket For visitors

For visitors

About this edition

About Data Expo

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About previous editions

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2026

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Partners

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Claim your free ticket

Visit Data Expo and achieve your data goals

Become an exhibitor

Become an exhibitor

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Become an exhibitor

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Become a partner

Giving a lecture

Testimonials

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Visitor profile

Contact the specialists

Request a brochure

All the information about exhibiting in one document.

Program

Program

About this edition

Program

Speakers

Giving a lecture

Testimonial speakers

Exhibitor list Blog & Knowledge

Blog & Knowledge

Discover

Blog

Featured

Women @ Data Expo

Diversity within the tech sector

Interview: "We are moving from data-driven to value-driven"

Joep Steenbeek | Head of Data Office | City of Amsterdam

Blog TicketSwap: "Right now, we are mainly focused on what we need to build"

Jessica Ruland | Lead Product Manager | TicketSwap

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Free ticket
Big Data Expo Vorm F (1) Big Data Expo Vorm E (1)

Experimentation, accelerated: what AI changes about the way we test

Wednesday 12:45 - 13:15
Lezingenzaal 2
Misha Datsenko

Senior Product Manager (Experimentation Analytics)

Linkedin Meer over deze spreker
AI is reshaping every step of the experimentation lifecycle — from generating hypotheses to interpreting results and turning them into actionable recommendations. What used to take days of back-and-forth between data teams, product managers, and engineers is increasingly something an AI agent can orchestrate end-to-end.

In this session, we explore how AI is automating the repetitive parts of testing, dramatically lowering the bar for teams to run high-quality experiments at scale, and shifting the data analyst's role from test executor to learning architect. We'll look at where are the most experimentation programs bottlenecked and what AI has to offer there.
AI is reshaping every step of the experimentation lifecycle — from generating hypotheses to interpreting results and turning them into actionable recommendations. What used to take days of back-and-forth between data teams, product managers, and engineers is increasingly something an AI agent can orchestrate end-to-end.

In this session, we explore how AI is automating the repetitive parts of testing, dramatically lowering the bar for teams to run high-quality experiments at scale, and shifting the data analyst's role from test executor to learning architect. We'll look at where are the most experimentation programs bottlenecked and what AI has to offer there.

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