Data Neighbor Podcast

In this episode of Data Neighbor, we’re joined by Nate Nichols, VP of Product at Tableau, to unpack how AI is changing analytics, not in theory, but in practice.🔗 Links & ResourcesData Neighbor: https://dataneighbor.comAI Analytics for Builders (course): https://bit.ly/analyst-aiFree 30-day AI Evals course: https://dataneighbor.kit.com/b595040b93Tableau Blog: https://www.tableau.com/blogConnect 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 Nate:https://www.linkedin.com/in/nate-nichols/Nate walks us through Tableau’s shift to proactive, agentic analytics: systems that detect meaningful changes, run diagnostic analysis, surface context, and push insights directly into the tools teams already use.We talk about:- Why the “last mile” of analytics has always been broken- How semantic models unlock trustworthy AI-driven analysis- What agentic analytics actually looks like in production- Where human judgment still matters as AI takes on more of the workflow- How analyst roles are evolving as insight moves closer to actionThis conversation changed how we think about the timeline for agentic analytics. It’s not years away, it’s already here.Chapters:00:00 Introduction to AI and data analytics00:31 Nate Nichols’ journey in AI and analytics00:59 The evolution of analytics and Tableau’s role02:42 Understanding user needs and data familiarity04:52 The pressure on analysts and business users07:33 The analytics pipeline and where value is lost10:16 Using AI to drive real outcomes13:03 Measuring success beyond dashboards15:49 What generative AI unlocks for analytics18:24 Trust, governance, and AI-driven insights24:36 Rolling out AI without breaking trust26:25 GenAI features inside Tableau28:10 Live demo: AI-powered analytics in Tableau33:47 Proactive analytics, alerts, and agents39:31 The future of analytics and human judgment57:19 Outro#dataneighbor #analytics #ai #agenticanalytics #tableau #datascience #dataanalytics #aievals #productanalytics

In this episode of Data Neighbor, we’re joined by Rami Abi Habib, CEO and co-founder of Querio, to talk about what agentic analytics looks like when it’s built into a BI product from the ground up.🔗 Links & ResourcesCheck out Querio: https://querio.ai/A ➞ B Podcast:  @QuerioData  Free AI workshops schedule: https://dataneighbor.comAI Analytics for Builders (course): https://bit.ly/analyst-aiFree 30-day AI Evals course: https://dataneighbor.kit.com/b595040b93Connect 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 Rami: https://www.linkedin.com/in/datarami/We talk about:* Why dashboards became the wrong default for “data-driven” teams* How agentic analytics changes the ticketing model for data teams* Why “BI as code” matters for transparency and trust* The semantic layer and context flywheel: how systems improve week over week* Where human judgment still matters (metrics, definitions, exceptions, executive trust)* What self-serve analytics does to data literacy across the business* What it will take to reach a “prompt is the dashboard” worldChapters:00:00 Introduction to Data Analysis in the AI Era04:18 Rami's Journey and Insights from Amazon09:08 The Birth of Querio: Addressing BI Challenges12:28 Understanding Querio: A New Approach to Data13:26 Governance and Trust in Data Analytics16:14 Workflow and User Experience with Querio22:53 Future Innovations and Enhancements in Querio25:47 Understanding Data Context and Metrics27:27 The Role of Documentation in Data Management28:46 Pilot Programs and Customer Onboarding29:49 The Shift Towards Self-Service Data31:58 Rethinking Dashboards and Data Access36:51 The Future of Data Tools and AI Integration38:33 Building a Strong Data Layer41:32 Challenges in Data Integration and Management46:38 Outro#dataneighbor #analytics #ai #agenticanalytics #querio #datascience #dataanalytics #productanalytics #aievals

Become and Expert in Agentic Analytics and AI Evals at https://dataneighbor.com/Learn more about Index:https://index.app/In this episode of the Data Neighbor Podcast, we sit down with Xavier Pladevall, co-founder of Index, to break down what’s actually changing in business intelligence and what’s not as AI enters the analytics stack.Index is building an AI-powered data platform that blends dashboards, SQL, and an agentic chat experience. But as Xavier explains, the hard parts of data work still show up in the same places: messy data, unclear questions, and getting a room of humans to trust and act on what they see.
In this episode, you’ll learn:- Why most “modern data” talk is disconnected from what teams actually use day to day- Why dashboards remain the default interface for stakeholders- How product design and UI quality change trust in data- What Index 1.0 is solving today, and what Index 2.0 unlocks next- How Index 2.0 makes analytics more proactive with recommended questions- Where AI breaks in analytics and why data quality is still the bottleneck- Why “data slop” compounds AI errors in surprising ways- Why data scientists are not going anywhere, even as AI takes on more tasks- Why SQL is more important than ever, just more abstractedWhat the real future looks like beyond “chat with your data”

#datapodcast #analytics #businessintelligence #datatools #datascience #aiforanalytics #agenticanalytics #productanalytics #dataleadership #dataneighbor #index

Explore Data Neighbor free workshops on AI evaluation and agentic analytics (plus our live, hands on course): https://dataneighbor.com/Learn more about LiveDocs:https://livedocs.com/In this episode of the Data Neighbor Podcast, we sit down with Arsalan Bashir, founder and CEO of LiveDocs, to unpack one of the biggest shifts happening in data right now: tools that don’t just help you analyze data, but start doing parts of the analysis for you.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 Arsalan:https://www.linkedin.com/in/arslnb/In this episode, you’ll learn:- Why “chat with your data” is the wrong mental model for where analytics is headed- What an “AI data scientist” actually means in practice (and what it doesn’t)- Why context matters more than schema for getting correct results from AI-generated analysis- How LiveDocs blends notebooks, app-building, and agentic workflows in one workspace- What it looks like when AI automates the 0→80% of data work (aka “yak shaving”)- How scheduling, notifications, and lightweight automation change the day-to-day of analysis- Where AI can go wrong in data work, and how to design for trust and review- Why handoff between stakeholders and data teams is still the core bottleneck- What new skills will matter most for analysts and data teams as agentic tools become standard
#datapodcast #analytics #businessintelligence #datatools #datascience #aiforanalytics #agents #agenticanalytics #productanalytics #dataleadership #dataneighbor #livedocs

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
#datapodcast #analytics #businessintelligence #datatools #datascience #aiforanalytics #agents #agenticanalytics #aievals #productanalytics #dataleadership #dataneighbor #count