Explore Data Neighbor free workshops on AI evaluation and agentic analytics (plus our live, hands on course): https://dataneighbor.com/Learn more about Count:https://count.co/In this episode of the Data Neighbor Podcast, we sit down with Ollie Hughes, co founder and CEO of Count, to unpack why traditional BI often fails at the real job teams hire data for: making better decisions, faster.If you care about the future of analytics workflows, this is a must watch.Connect with the team (tell us YouTube sent you!):Shane Butler: https://linkedin.openinapp.co/b02feSravya Madipalli: https://linkedin.openinapp.co/9be8cHai Guan: https://linkedin.openinapp.co/4qi1rConnect with Ollie:https://www.linkedin.com/in/hughesoliver/In this episode, you’ll learn:- Why dashboards are not designed for collaborative decision making- What the “service trap” is and how it keeps data teams in reactive work- How operational clarity helps companies simplify what matters- Why a canvas based interface changes how teams reason with data- What collaborative analysis looks like in practice between analysts and stakeholders- How agile decision making can reduce time to insight and time to decision- How Count thinks about AI agents for analytics without black boxes- What skills will matter most for data teams as AI takes on more of the mechanical work

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