INTERACTIVE DECISION SCIENCE
Most organisations aim to be "data-driven" but never reflect on the true purpose of why data is collected - for making better decisions. However, how do we know what a "good" decision looks like?
Activities tracked
67
Superweek 2025 - Analytics conference in Hungary
Sessions & talks
Showing 26–50 of 67 · Newest first
Most organisations aim to be "data-driven" but never reflect on the true purpose of why data is collected - for making better decisions. However, how do we know what a "good" decision looks like?
Discover how the Digital Analytics team at Itaú, the largest private bank in Latin America, built a high-quality, unified, and standardized tagging ecosystem that simplified data collection, ensured consistent data quality across various measurement tools, and created a comprehensive, customer-centric data strategy across over 10 apps, thousands of developers, and hundreds of business operations.
We all know it. It’s only a question of time before some friendly soul will come and ask to have your analytics data added to their AI. And in theory that’s great. But what digital analytics data is not known for is quality and that is what AI needs.
I like to joke that I’m an expert on imposter syndrome—mostly because I’ve felt it in every aspect of my life. As a GA/GTM professional and, especially, as a guitarist in pit orchestras for musicals, I’ve spent plenty of time wondering if I belong. But those experiences have also taught me some ways to navigate self-doubt. In this talk, I’ll share stories, lessons, and a few laughs about finding confidence when you feel like a fraud. Who knows? Maybe being an imposter isn’t such a bad thing after all.
Automation has evolved from simple scripting to become an essential cornerstone of modern data workflows. However, automation isn't without its pitfalls. While promising to reduce workload and improve efficiency, poorly implemented automation can create technical debt, introduce hidden errors, require constant maintenance - and just drive you crazy.
Joining Dan, and Doug will be Russ, and many others from the conference to share what they look for in a productive business partnership. The dos and don'ts. The alarm bells and the warm fuzzy feelings of mutual commercial success.
Being tool-agnostic is more than a best practice—it’s a guiding principle for creating a sustainable and adaptable analytics strategy. By remaining equally adept with and unbiased toward various tools, analysts and organizations can prioritize meaningful insights and strategic outcomes over vendor-specific limitations or preferences.
Forget dashboards full of metrics—real insights start with asking the right questions. In this talk, we’ll go through a journey into how curiosity and bold questioning can flip your analytics game on its head. We will explore how to stop getting stuck in the weeds and start uncovering the insights that actually matter. It’s time to ditch the boring ‘data-driven’ buzzwords and get real about the power of smart, strategic questions. Ready to refresh the way you think about analytics?
Experience how Hilton’s research and experimentation team creates a lasting reverb of customer insight that influences each stage of design. Having grown from one part-time A/B tester to a robust insights-driven program, they amplify guest voices in each decision, ensuring the effects of research echo across all customer interactions.
In large enterprises, digital analytics teams face technical and organizational challenges, from managing multi-domain setups to navigating company politics and stakeholder relationships. This session explores how enterprises can build resilient analytics infrastructures and leverage advanced tracking setups for improved efficiency, while effectively managing and growing their teams in complex environments.
Using BigQuery for GA4 data is nothing new. We have all been exploring or weighing the capabilities of the export to some extent. And we have all been wondering.
It’s been more than 2 years since the advent of Large Language Models - the release of ChatGPT. Billions of dollars have been invested in GenAI, and all the media foreshadows the end of IT work as we know it.
As data analysts, we love to sink our teeth into building machine learning models. But for our clients, number crunching is only appealing if it improves their bottom line. A question we often hear from stakeholders is, "so what?"
Demonstrate any Digital Analytics solutions or method of your own that is way beyond the defaults. Who decides who's gonna win? The audience. Send your nomination to [email protected]!