Data Neighbor Podcast

Data Neighbor Podcast
  • 5.0(9개의 평가)
  • 과학 기술
  • 매주 업데이트

Welcome to the Data Neighbor Podcast with Hai, Sravya, and Shane! We’re your friendly guides to the ever-evolving world of data. Whether you’re an aspiring data scientist, a data professional looking to grow your career, or just curious about how data shapes the world, you’re in the right place. Our mission? To help you break in or thrive in the field of data. We dive into: - Personal career journeys and how luck, opportunity, and grit play a role - How to break into the data field even with a non-traditional background - Industry insights through engaging conversations and expert interviews

  1. 2월 19일

    Ep50: Tableau and the Rise of Proactive, Agentic Analytics

    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

    57분

  2. 2월 12일

    Ep49: How Querio Uses AI to Replace Dashboards With Answers

    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

    47분

  3. 2월 5일

    Ep48: The Rise of the AI Analyst with CEO of Index

    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

    56분

  4. 1월 29일

    Ep47: How LiveDocs Is Automating Data Science with Agentic AI

    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

    52분

  5. 1월 23일

    Ep46: How Collaborative AI Analytics Revamp Data Work

    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

    1시간

  6. 2025. 12. 19.

    Ep45: Starting a Podcast: What We Got Wrong, What We Learned, and What’s Next

    Join Our Upcoming AI Evals Cohort! https://maven.com/dataneighbor/ai-evalsSubscribe to our newsletter: https://dataneighbor.substack.com/DNP Swag Store: https://shop.dataneighbor.com/In this episode of the Data Neighbor Podcast, we do something different. No guest. Just the three of us reflecting on what we learned after a year of running the show.We talk honestly about what surprised us most, what turned out to be harder than expected, and why the “real work” of podcasting is everything around the recording: editing, publishing, distribution, and yes, thumbnails.We also dig into what hosting a podcast has done for our careers: better communication reps, more surface area in the industry, and a faster growing network than we expected.Finally, we share a preview of what we are building in 2026, including two big themes we keep seeing across the industry: AI product evaluation and AI powered analytics.If you are thinking about starting a podcast, already building one, or just want a candid behind the scenes look at what it takes to stay consistent for a full year, this episode is for you.Connect with the team (tell us which platform sent you!):Shane Butler: https://linkedin.openinapp.co/b02feSravya Madipalli: https://linkedin.openinapp.co/9be8cHai Guan: https://linkedin.openinapp.co/4qi1rIn this episode, you’ll learn:- What nobody tells you about the time investment behind a podcast- Why consistency is the hardest part, and how to design for it- How having multiple co hosts reduces burnout and improves the show- How podcasting can expand your network and professional opportunities- What we learned from a year of interviewing builders and operators- What we are focusing on in 2026: AI evaluation and AI powered analytics #podcasting #podcast #creator #contentcreation #careergrowth #networking #aiproduct #aievaluation #analytics #datascience #dataneighbor

    36분

  7. 2025. 12. 12.

    Ep44: The Future of AI Teams - Research, Product, and Domain Expertise

    In this episode of the Data Neighbor Podcast, we sit down with Shelby Heinecke, PhD, Senior AI Research Manager at Salesforce, to break down what modern AI teams actually look like and how enterprise AI gets built in practice.Shelby shares how her team moves research into production, why small crisp problem definitions outperform ambitious abstractions, and how evaluation before development has become a non negotiable part of the workflow.We also talk about the shifting shape of AI teams, the rising importance of domain experts, and why interdisciplinary collaboration is quickly becoming the core of the field.If you want an inside look at how leading AI orgs actually operate, this is the episode.Connect with the team (tell us which platform sent you!): - Sravya Madipalli: https://linkedin.openinapp.co/9be8c- Shane Butler: https://linkedin.openinapp.co/b02fe - Hai Guan: https://linkedin.openinapp.co/4qi1r Connect with Shelby:https://www.linkedin.com/in/shelby-heinecke/In this episode, you’ll learn:- How enterprise AI research teams actually set direction- Why crisp scope and early evaluation decide which projects reach production- What makes interdisciplinary collaboration essential for AI success- How small models and agents are being deployed across Salesforce- What skills matter most for the next generation of AI roles- Why embodied agents may represent the next major leap in AI#aipodcast #airesearch #salesforce #aiteams #aiproducts #llm #datascience #mlengineering #aidevelopment #agents #embodiedai #dataneighbor #aifuture

    46분

  8. 2025. 12. 05.

    Ep43: Building Women in Data: Sadie’s Playbook for Starting Movements

    Join us for an inspiring conversation with Sadie St Lawrence, founder and CEO of Women in Data, and the Human Machine Collaboration Institute! Sadie shares her incredible journey from piano and neuroscience to pioneering a global movement empowering tens of thousands of women in data and AI. Discover her unique insights on building impactful communities, navigating career changes, and the evolving role of humans in the age of AI.In this episode, we cover:- Sadie's fascinating career trajectory, from a neuroscience lab to a data science pioneer and community builder.- The origin story of Women in Data, starting from a personal need for community to a global movement of 70,000 members across 120+ countries.- The critical role of consistency and trust in building a thriving community and achieving professional growth.- The current landscape of diversity in data careers, with eye-opening statistics and the significant impact of female leadership.- Sadie's visionary perspective on the future of work, where humans become "orchestra conductors" in a world augmented by AI.- The mission of the Human Machine Collaboration Institute (HMCI) in tackling fundamental questions about humanity, emotion, and consciousness in the AI era.- Practical advice on cultivating curiosity, breaking patterns, and leveraging your innate desire to learn for career advancement and personal fulfillment.Whether you're looking to start a community, advance your career in data, or curious about the philosophical implications of AI, Sadie's story and insights offer invaluable lessons. Tune in to understand why consistency, community, and curiosity are your greatest assets in the rapidly changing world of technology.Connect with Hai, Sravya, and Shane (let us know which platform sent you!):- Hai: https://www.linkedin.com/in/hai-guan-6b58a7a/- Sravya: https://www.linkedin.com/in/sravyamadipalli/- Shane: https://www.linkedin.com/in/shaneausleybutler/#DataScience #AI #WomenInData #CareerAdvice #TechLeadership #CommunityBuilding #HumanMachineCollaboration #Curiosity #DiversityInTech #Neuroscience #Consciousness #FutureOfWork #DataCareers #STEM #ProfessionalDevelopment #Podcast #DataNeighbor

    50분
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Welcome to the Data Neighbor Podcast with Hai, Sravya, and Shane! We’re your friendly guides to the ever-evolving world of data. Whether you’re an aspiring data scientist, a data professional looking to grow your career, or just curious about how data shapes the world, you’re in the right place. Our mission? To help you break in or thrive in the field of data. We dive into: - Personal career journeys and how luck, opportunity, and grit play a role - How to break into the data field even with a non-traditional background - Industry insights through engaging conversations and expert interviews

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  • 제작진
    Data Neighbor Podcast
  • 방송 연도
    2024년 - 2026년
  • 에피소드
    50
  • 등급
    전체 연령 사용가
  • 저작권
    © Data Neighbor Podcast
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    Data Neighbor Podcast