Shachar Meir

The analytics profession is undergoing its most disruptive shift in a decade. Larger and more complex datasets, the rapid adoption of AI and automation, and an increasingly volatile business environment are forcing a fundamental question: what is the analytics team actually for? The teams that thrive won't be those with the best tools – they'll be the ones who make the leap from producing reports to shaping decisions. Drawing on real-world case studies, this talk makes the case that the defining skill of the next generation of analytics professionals isn't technical – it's influence. Regardless of your role (Data Engineer, Data Scientist, an Analyst, ...) – you must adjust. Attendees will leave with a practical framework for approaching their role, concrete examples of how leading organisations have already made this shift, and a clear-eyed view of the traps that cause capable data professionals to fall behind.

For years, data teams have measured themselves by technical excellence: pipelines built, dashboards shipped, tickets closed, models and insights delivered. But in a shift-left world where business users increasingly do the work themselves, technical delivery is no longer a differentiator. It's table stakes. This roundtable makes a provocation: the order-taking data team is ending. What replaces it? What is a data function uniquely for when the business can self-serve? And what does that demand of the CDO – a role that must shift from running delivery to driving value? We'll explore: Where does order-taking still persist in your organisation – and why? If the business can self-serve, what is the data team for? What does "driving value" look like in practice, beyond the slogan? How do the CDO's skills, mandate, and metrics need to reset? You'll leave with a sharper view of where your team sits on the order-taker-to-value-driver spectrum, and concrete moves your peers are making that keep them relevant in 2027 and beyond. No slides, no vendor pitches – just an honest conversation between data leaders about the future of our role.

We're living a time of uncertainty and tectonic changes, in our industry and the way we do business. From how we work, to macro-economics and politics, unstable job market, and evolving technological landscape.

Practicing analytics well takes more than just tools and tech. It requires data modeling practices that unify and empower all teams within analytics, from engineers to analysts. This is especially true as AI becomes a part of analytics. Without a governed data model that provides consistent data interpretation, AI tools are left to guess. Join panelists Joe Reis, Sarah Levy, Harry Gollop, Rob Hulme, Shachar Meir, and Guy Fighel, as they share battle-tested advice on overcoming conflicting definitions and accurately mapping business intent to data, reports and dashboards at scale. This panel is for data & analytics engineers seeking a clear framework to capture business logic across layers, and for data leaders focused on building a reliable foundation for Gen AI.

Many Data Engineers play very reactive roles. Because of that they struggle with cross-org collaboration, getting a seat at the table, creating alignment, and making their data producers produce high-quality data for them. But there's another way – Data Engineers can LEAD! Data Engineers sit at the intersection of data and their business, and if they execute well, they can play a very pivotal role! In this talk, Orr and Shachar will explain what it looks like when you lead as a Data Engineer, and give practical suggestions for ways to apply that in your job.