The world has never been more connected. Today, customers demand near-perfect uptime, responsive networks, and personalized digital experiences from their telecommunications providers. 

The industry has reached an inflection point. Legacy architectures, fragmented customer data, and batch-based analytics are no longer sufficient. Now is the time for Telcos to embrace real-time, when the speed of insights and the ability to remain agile determine competitive advantage.

In this session, leaders from Orange Belgium, Google Cloud, and Striim explore how telcos can rethink their data foundations to become real-time, intelligence-driven enterprises. From centralizing data in BigQuery and Spanner to enabling dynamic customer engagement and scalable operations, Orange Belgium shares how its cloud-first strategy is enabling agility, trust, and innovation.

This isn’t just a story of technology migration—it’s about building a data culture that prioritizes immediacy, empathy, and evolution. Join us for a forward-looking conversation on how telcos can align infrastructure, intelligence, and customer intent.

Ten years ago, I began advocating for **DataOps**, a framework designed to improve collaboration, efficiency, and agility in data management. The industry was still grappling with fragmented workflows, slow delivery cycles, and a disconnect between data teams and business needs. Fast forward to today, and the landscape has transformed, but have we truly embraced the future of leveraging data at scale? This session will reflect on the evolution of DataOps, examining what’s changed, what challenges persist, and where we're headed next.

**Key Takeaways:**

✅ The biggest wins and ongoing struggles in implementing DataOps over the last decade. 

✅ Practical strategies for improving automation, governance, and data quality in modern workflows. 

✅ How emerging trends like AI-driven automation and real-time analytics are reshaping the way we approach data management. 

✅ Actionable insights on how data teams can stay agile and align better with business objectives. 

**Why Attend?**

If you're a data professional, architect, or leader striving for operational excellence, this talk will equip you with the knowledge to future-proof your data strategies.

Development teams often embrace Agile ways of working, yet the systems we build can still struggle to adapt when business needs shift. In this talk, we’ll share the journey of how a cross-functional data science team at the LEGO Group evolved its machine learning architecture to handle real-world complexity and change.

We’ll highlight how new modelling strategies, advanced feature engineering, and modern MLOps pipelines were designed not only for performance, but for flexibility. You’ll gain insight into how we architected a resilient ML system that supports changing requirements, scales with ease, and enables faster iteration. Expect actionable ideas on how to future-proof your own ML solutions and ensure they remain relevant in dynamic business contexts.

Powered by: Women in Data®

This session will explore Merlin Entertainments’ data transformation journey in partnership with Telefónica Tech. Starting from a position of minimal governance and limited internal capability, Merlin Entertainments has built a federated data strategy, implemented agile data product teams, and delivered impactful use cases such as the Genie AI. This talk will highlight how Merlin Entertainments developed a partner-agnostic delivery model to embed expertise and drive business value. Attendees will gain practical insights into structuring data teams, overcoming transformation hurdles, and leveraging partnerships to innovate at scale.

How long will it be until an AI first company dominates your industry? Could that disrupter be your business? 

In this keynote, Gareth Martin (CEO of Manuka AI) and Maria Bines (CEO and co-founder of SynapseDX) will challenge comfortable assumptions about how AI should be used. Maria will share how she turned AI agents into a working scrum team — complete with job descriptions, an org chart, and the messy lessons of managing digital workers who don’t behave like humans. Gareth will explore why today’s obsession with “use cases” is a band-aid, and why process-driven adoption is the only way to avoid being disrupted — or irrelevant. 

This session isn’t about safe platitudes. It’s about what’s really happening in the wild, what technical professionals need to prepare for, and why the future of AI could look like seamless orchestration… or a chaotic swarm.

Reason why Data should be the Fourth Pillar for every enterprise. The Board, CEOs, and CxOs must understand why they should treat data strategically. Enterprises’ use cases like AI drive the need for data high in quality, compliance, and speed dimensions. 

- Present a framework for enterprises to understand their current data challenges. 

- Key principles for the data pillar 

- Role of the Chief Data Officer (CDO) - nurture demand for data while taking steps to fulfill the supply of demand through an agile data operating model (DOM). The DOM enabled by people, processes, and technologies. 

- Measuring the impact provided by the data pillar, introduce KPIs such as Total Addressable Value through data (TAV) and Expected Addressable Value through data (EAV). 

- A Maturity Framework for every enterprise to track and progress its data maturity journey.