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Spatial computing is revolutionizing the way we interact with digital and physical worlds, but its adoption comes with questions about practicality and return on investment. As businesses explore this cutting-edge technology, they must consider how it can enhance productivity and streamline operations. What are the best strategies to integrate spatial computing into your current systems? How can you ensure that it not only boosts efficiency but also delivers measurable benefits to your bottom line?  Cathy Hackl is a web3 and metaverse strategist, tech futurist, speaker and author. She's worked with metaverse-related companies such as HTC VIVE, Magic Leap, and AWS, and currently consults with some of the world's leading brands, including P&G, Clinique, Ralph Lauren, Orlando Economic Partnership and more. Hackl is one of the world's first Chief Metaverse Officers and the co-founder of Journey, where she works with luxury, fashion, and beauty brands to create successful metaverse and web3 strategies and helps them build worlds in platforms like Roblox, Fortnite, Decentraland, The Sandbox, and beyond. She is widely regarded as one of the leading thinkers on the Metaverse. Irena Cronin is SVP of Product for DADOS Technology, which is making an Apple Vision Pro data analytics and visualization app. She is also the CEO of Infinite Retina, which helps companies develop and implement AI, AR, and other new technologies for their businesses. Before this, she worked as an equity research analyst and gained extensive experience in evaluating both public and private companies. In the episode, Richie, Cathy and Irina explore spatial computing, the current viability of spacial computing and it's prominence alongside the release of Apple's Vision Pro, expected effects of spatial computing on gaming and entertainment, industrial applications as well as data visualization and AI integration opportunities of spatial computing, how businesses can leverage spatial computing, future developments in the space and much more.  Links Mentioned in the Show: Cathy’s BookIrena’s BooksApple Vision ProMarvel Studios and ILM Immersive Announce 'What If...? - An Immersive Story'[Course] Artificial Intelligence (AI) StrategyRelated Episode: Why the Future of AI in Data will be Weird with Benn Stancil, CTO at Mode & Field CTO at ThoughtSpotSign up to RADAR: AI Edition New to DataCamp? Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

If everything goes the way that the experts say it will, Generative AI will eventually be a core part of nearly every piece of technology we use. But before that happens, some organizations will likely make their current products worse, as they try to integrate GenAI functionality in their existing services. Join Benn Stancil, Field CTO at ThoughtSpot, to strategize which Generative AI dreams are worth chasing, what foundations you need to build and leverage AI, and how to take advantage of these AI developments while avoiding major disasters. 

Benn Stancil, cofounder and CTO at Mode, returns to The Analytics Engineering Podcast to discuss the evolution of the term "modern data stack" and its value today. Tristan wrote on this idea for The Analytics Engineering Roundup in Is the Modern Data Stack Still a Useful Idea? For full show notes and to read 6+ years of back issues of the podcast's companion newsletter, head to https://roundup.getdbt.com. The Analytics Engineering Podcast is sponsored by dbt Labs.

*** RSVP here to receive joining link: https://www.aicamp.ai/event/eventdetails/W2024011615

Benn Stancil is the Field CTO at ThoughtSpot. He joined in 2023 as part of its acquisition of Mode, a collaborative data platform that combines SQL, R, Python, and visual analytics in one place, where he was a co-founder and CTO.

​In this fireside chat, Benn joins Hugo Bowne-Anderson, Outerbounds’ Head of Developer Relations, to talk about the intersection of data, analytics, modern BI tools, the modern data stack,and AI. They’ll discuss:

• ​The modern data stack and the tooling landscape;
• Arguments for and against unbundled and bundled data stacks;
• The future of roles in the space: what will happen to data engineers, analytics engineers, ML engineers, and BI analysts? Who is going to stay? What roles are going to merge?
• The role of data in the future of GenAI products;
• How AI will change data-driven products and analytic tools!
• And much more. *

*** RSVP here to receive joining link: https://www.aicamp.ai/event/eventdetails/W2024011615

Benn Stancil is the Field CTO at ThoughtSpot. He joined in 2023 as part of its acquisition of Mode, a collaborative data platform that combines SQL, R, Python, and visual analytics in one place, where he was a co-founder and CTO.

​In this fireside chat, Benn joins Hugo Bowne-Anderson, Outerbounds’ Head of Developer Relations, to talk about the intersection of data, analytics, modern BI tools, the modern data stack,and AI. They’ll discuss:

• ​The modern data stack and the tooling landscape;
• Arguments for and against unbundled and bundled data stacks;
• The future of roles in the space: what will happen to data engineers, analytics engineers, ML engineers, and BI analysts? Who is going to stay? What roles are going to merge?
• The role of data in the future of GenAI products;
• How AI will change data-driven products and analytic tools!
• And much more. *

Data engineers build critical pipelines that underpin the computational infrastructure that powers our global economy. Analytics engineers translate impossibly complex business semantics into precise frameworks that give modern companies digital eyes and ears, making them the most agile and responsive organizations ever created. Data scientists find revolutionary truths among vast expanses of noise and distraction, unearthing tiny diamonds in endless mines of numerical dirt.

This talk isn’t about any of that.

This talk is about commas. It’s about capitalization. It’s about indentation. It’s about the tedious arguments that no sensible person should ever care about, but we, as data people, can’t seem to resist. It’s about indulging in our unhinged debates, analyzing data on billions of queries, and giving us all a reason to bury our flag a bit deeper into whatever petty hill we’ve each chosen to die on. Let the good times roll.

Will it tell us anything useful? No. Will there be slides that you can take pictures of to show your leadership team why your role is valuable? Absolutely not. But there will be lots of charts , graphs , and misplaced commas.

Speaker: Benn Stancil, CTO, Mode

Register for Coalesce at https://coalesce.getdbt.com

Send us a text Want to be featured as a guest on Making Data Simple? Reach out to us at [[email protected]] and tell us why you should be next.

Abstract Making Data Simple Podcast is hosted by Al Martin, VP, IBM Expert Services Delivery, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun. This week on Making Data Simple, we have Benn Stancil, Chief Analytics Officer + Founder @ Mode. Benn is an accomplished data analyst with deep expertise in collaborative Business Intelligence and Interactive Data Science. Benn is Co-founder, President, and Chief  Analytics Officer of Mode, an award-winning SaaS company that combines the best elements of Business Intelligence (ABI), Data Science (DS) and Machine Learning (ML) to empower data teams to answer impactful questions and collaborate on analysis across a range of business functions. Under Benn’s leadership, the Mode platform has evolved to enable data teams to explore, visualize, analyze and share data in a powerful end-to-end workflow. Prior to founding Mode, Benn served in senior Analytics positions at Microsoft and Yammer, and worked as a  researcher for the International Economics Program at the Carnegie Endowment for International Peace. Benn also served as an Undergraduate Research Fellow at Wake Forest University,  where he received his B.S. in Mathematics and Economics. Benn believes in fostering a shared sense of humility and gratitude.

Show Notes 1:22 – Benn’s history7:09 – Tell us how you got to where you are today9:14 – Tell us about Mode12:08 – What is your definition of the Chief Analytics Officer?21:53 – Why do we need another BI tool?24:09 – What’s your secret sauce?27:48 – Where did the name Mode come from?28:41 – How do we use Mode?31:08 – What is you goto market strategy? 32:38 – Any client references?34:58 – “The missing piece in the modern data stack” tell us about thisMode  Email: [email protected] [email protected] Twitter: benn stancil Connect with the Team Producer Kate Brown - LinkedIn. Host Al Martin - LinkedIn and Twitter.  Want to be featured as a guest on Making Data Simple? Reach out to us at [email protected] and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.

Most analysts don’t become analysts to build dashboards. We don’t become analysts to do data pulls, or clean up messy data, or put together pitch decks. We become analysts to do impactful, strategic analysis. This is our calling; it’s the most valuable work that we do; and it’s why we put up with the rest of our job—for that afternoon with nothing but a big question, a clear calendar, and a trajectory-changing aha moment buried somewhere in our well-prepped datasets.

But the rapid rise of analytics engineering should make us question all of this. Is strategic analysis actually the holy grail of analytics? Is it the most valuable thing we could do? Is it even what we want to do?

In chasing this ambition, Benn Stancil (Mode) thinks we’ve lost sight of something even more important—and potentially, more interesting: Designing operational models. These frameworks, which are a natural extension of the semantic models built by analytics engineers, are often more valuable than any dashboard, any dataset, or any deep dive analysis.

In his talk, Benn will share what these models are, why they’re valuable, and why, in our eternal quest to both quantify our value and to find work we love, they could prove to be our holy grail we’ve always been looking for.

Check the slides here: https://docs.google.com/presentation/d/1lOH6Sb8DQnnlmZkYOlqqHgQeXKkUEQCm_LOxsjBRJlM/edit?usp=sharing

Coalesce 2023 is coming! Register for free at https://coalesce.getdbt.com/.

Every company, regardless of size, is dealing with a barrage of data. In any typical organisation, there is more information on hand than we know how to use or manage. While every team in the organisation is screaming for analytics professionals to turn data into insight, a strong data and analytics tech stack is foundational to being able to make sense of it all. The need for a robust and efficient data and analytics tech stack has created a sprawling industry for new technology solutions that sell the promise of seamless integration and faster insights. Today, there are a plethora of data and analytics platforms available, most with very high valuations attached to them. But do we really need all these tools to make us super-powered data users? To answer this question and many more related to the data and analytics tech stack, I recently spoke to Benn Stancil. Benn is the co-founder and Chief Analytics Officer at Mode. Mode is a modern analytics and BI solution that combines SQL, Python, R and visual analysis to answer questions for its users. In this episode of Leaders of Analytics, you will learn: What the perfect analytics tech stack looks like and why.Programmatic automation of the analytics workflow.What will cutting-edge analytics tech be able to do 5-10 years from now.Why Been thinks the Chief Analytics Officer role should be redefined, and much more.Connect with Benn Benn on LinkedIn: https://www.linkedin.com/in/benn-stancil/ Benn on Twitter: https://twitter.com/bennstancil Benn's (brilliant) Substack blog: https://benn.substack.com/

"Modern art" was a terrible label because, ya' know, time would pass and here we are 50 years after the end of that period shaking our heads at what a short-sighted semantic gaff that was. We share that observation for no particular reason. On this episode, we sat down with broad, deep, and entertaining thinker Benn Stancil from Mode to talk about one facet of the modern data stack: the metrics layer. What is it? Who's thinking about solving for it? What is a monthly DAU? These are questions to ponder that, hopefully, won't leave you impersonating a piece of modern art. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

A debate has erupted on data Twitter and data Substack - should the modern data stack remain unbundled, or should it consolidate? In this conversation, Benn Stancil (Mode), David Jayatillake (Avora) and our host Tristan Handy try to make some sense of this debate, and play with various future scenarios for the modern data stack.  For full show notes and to read 6+ years of back issues of the podcast's companion newsletter, head to https://roundup.getdbt.com.  The Analytics Engineering Podcast is sponsored by dbt Labs.

Summary This has been an active year for the data ecosystem, with a number of new product categories and substantial growth in existing areas. In an attempt to capture the zeitgeist Maura Church, David Wallace, Benn Stancil, and Gleb Mezhanskiy join the show to reflect on the past year and share their thought son the year to come.

Announcements

Hello and welcome to the Data Engineering Podcast, the show about modern data management When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode. With their managed Kubernetes platform it’s now even easier to deploy and scale your workflows, or try out the latest Helm charts from tools like Pulsar and Pachyderm. With simple pricing, fast networking, object storage, and worldwide data centers, you’ve got everything you need to run a bulletproof data platform. Go to dataengineeringpodcast.com/linode today and get a $100 credit to try out a Kubernetes cluster of your own. And don’t forget to thank them for their continued support of this show! Struggling with broken pipelines? Stale dashboards? Missing data? If this resonates with you, you’re not alone. Data engineers struggling with unreliable data need look no further than Monte Carlo, the world’s first end-to-end, fully automated Data Observability Platform! In the same way that application performance monitoring ensures reliable software and keeps application downtime at bay, Monte Carlo solves the costly problem of broken data pipelines. Monte Carlo monitors and alerts for data issues across your data warehouses, data lakes, ETL, and business intelligence, reducing time to detection and resolution from weeks or days to just minutes. Start trusting your data with Monte Carlo today! Visit dataengineeringpodcast.com/montecarlo to learn more. The first 10 people to request a personalized product tour will receive an exclusive Monte Carlo Swag box. Are you bored with writing scripts to move data into SaaS tools like Salesforce, Marketo, or Facebook Ads? Hightouch is the easiest way to sync data into the platforms that your business teams rely on. The data you’re looking for is already in your data warehouse and BI tools. Connect your warehouse to Hightouch, paste a SQL query, and use their visual mapper to specify how data should appear in your SaaS systems. No more scripts, just SQL. Supercharge your business teams with customer data using Hightouch for Reverse ETL today. Get started for free at dataengineeringpodcast.com/hightouch. Your host is Tobias Macey and today I’m interviewing Maura Church, David Wallace, Benn Stancil, and Gleb Mezhanskiy about the key themes of 2021 in the data ecosystem and what to expect for next year

Interview

Introduction

How did you get involved in the area of data management?

What were the main themes that you saw data practitioners and vendors focused on this year?

What is the major bottleneck for Data teams in 2021? Will it be the same in 2022? One of the ways to reason about progress in any domain is to look at what was the primary bottleneck of further progress (data adoption for decision making) at different points in time. In the data domain, we have seen a number of bottlenecks, for example, scaling data platforms, the answer to which was Hadoop and on-prem columnar stores and then cloud data warehouses such as Snowflake & BigQuery. Then the problem was data integration and transformation which was solved by data integration vendors and frameworks such as Fivetran / Airbyte, modern orchestration frameworks such as Dagster & dbt and “reverse-ETL” Hightouch. What is the main challenge now?

Will SQL be challenged as a primary interface to analytical data? In 2020 we’ve seen a few launches of post-SQL languages such as Malloy, Preql, metric layer query languages from Transform and Supergrain.

To what extent does speed matter? Over the past

Send us a text Want to be featured as a guest on Making Data Simple? Reach out to us at [[email protected]] and tell us why you should be next.

Abstract Making Data Simple Podcast is hosted by Al Martin, VP, IBM Expert Services Delivery, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun. This week on Making Data Simple, we have Benn Stancil, Chief Analytics Officer + Founder @ Mode. Benn is an accomplished data analyst with deep expertise in collaborative Business Intelligence and Interactive Data Science. Benn is Co-founder, President, and Chief  Analytics Officer of Mode, an award-winning SaaS company that combines the best elements of Business Intelligence (ABI), Data Science (DS) and Machine Learning (ML) to empower data teams to answer impactful questions and collaborate on analysis across a range of business functions. Under Benn’s leadership, the Mode platform has evolved to enable data teams to explore, visualize, analyze and share data in a powerful end-to-end workflow. Prior to founding Mode, Benn served in senior Analytics positions at Microsoft and Yammer, and worked as a  researcher for the International Economics Program at the Carnegie Endowment for International Peace. Benn also served as an Undergraduate Research Fellow at Wake Forest University,  where he received his B.S. in Mathematics and Economics. Benn believes in fostering a shared sense of humility and gratitude.

Show Notes 1:22 – Benn’s history 7:09 – Tell us how you got to where you are today 9:14 – Tell us about Mode 12:08 – What is your definition of the Chief Analytics Officer? 21:53 – Why do we need another BI tool? 24:09 – What’s your secret sauce? 27:48 – Where did the name Mode come from? 28:41 – How do we use Mode? 31:08 – What is you goto market strategy?  32:38 – Any client references? 34:58 – “The missing piece in the modern data stack” tell us about this Mode  Email: [email protected] [email protected] Twitter: benn stancil Connect with the Team Producer Kate Brown - LinkedIn. Producer Steve Templeton - LinkedIn. Host Al Martin - LinkedIn and Twitter.  Want to be featured as a guest on Making Data Simple? Reach out to us at [email protected] and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.

In this video, President and Founder of Mode, Benn Stancil discusses new ways to align the optimal application boundaries in the modern data stack, providing a set of guidelines for determining how and where to draw the lines between your many tools. He also motivates an example of these boundaries by demonstrating how metadata surfaced in an analytics tool like Mode can increase overall data confidence.