The Analytics Engineering Podcast

The Analytics Engineering Podcast

By dbt Labs, Inc.NewsTechnologyTech News
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The Analytics Engineering Podcast episodes

  • Coalesce 2024 edition: What's next for data teams? (w/ Scott Breitenother)

    Show description: Scott Breitenother, founder of data consultancy Brooklyn Data Co., joins Tristan at Coalesce 2024 in Las Vegas to discuss the early days of dbt, the evolution of data teams, and what's next for the dbt community.

    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.

    45 min
  • The current state of the AI ecosystem (w/ Julia Schottenstein)

    Former co-host Julia Schottenstein returns to the show to go deep into the world of LLMs. Julia joined LangChain as an early employee, in Tristan's words, to "Basically solve all of the problems that aren't specifically in product and engineering." LangChain has become one of, if not the primary frameworks for developing applications using large language models. There are over a million developers using LangChain today, building everything from prototypes to production AI applications.

    46 min
  • Creating value from GenAI in the enterprise (w/ Nisha Paliwal)

    Nisha Paliwal, who leads enterprise data tech at Capital One, joins Tristan to discuss building a strong data culture for in the world of AI. She is the co-author of the book Secrets of AI Value Creation.

    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.

    46 min
  • Developer productivity on GitHub Copilot (w/ Eirini Kalliamvakou)

    Dr. Eirini Kalliamvakou is a senior researcher at GitHub Next. Eirini has built a career on studying software engineers, how to measure their productivity, how developer experience impacts productivity, and more.

    Recently, Eirini has been working on quantifying the impacts of GitHub Copilot. Does it actually help software engineers be more productive? Tristan and Eirini explore how to quantify developer productivity in the first place, and finally, arriving at whether or not Copilot‌ makes a difference. In the search for real business value, this research is a real bellwether of things to come.

    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.

    Join data practitioners and data leaders this October in Las Vegas at Coalesce, the analytics engineering conference hosted by dbt Labs. Register now at coalesece.getdbt.com. Listeners of this show can use the code podcast20 for a 20% discount.

    54 min
  • The rapid experimentation of AI agents (w/ Yohei Nakajima)

    Yohei Nakajima is an investor by day and coder by night. In particular, one of his projects, an AI agent framework called BabyAGI that creates a plan-execute loop, got a ton of attention in the past year.

    The truth is that AI agents are an extremely experimental space, and depending on how strict you want to be with your definition, there aren't a lot of production use cases today.

    Yohei discusses the current state of AI agents and where they might take us.

    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.

    46 min
  • Funnel analytics and AI models for event sequences (w/ Misha Panko)

    Misha Panko has worked in data for a long time, including on high performance data teams at Uber and Google. Today, Misha is the co-founder and CEO of Motif Analytics, a product focused on helping growth and ops teams understand their event data.

    In this episode, Tristan and Misha nerd out about the state of the art in computational neuroscience, where Misha got his PhD. They then go deep into event stream data and how it differs from classical fact and dimension data, and why it needs different analytical tools.

    Make sure to check out the back half of the episode, where they dive into AI and how Motif is applying breakthroughs in language modeling to train foundation models of event sequences—check out his team's blog post on their work.

    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.

    45 min
  • From Moneyball to Gen AI

    Eric Avidon is a journalist at TechTarget who's interviewed Tristan a few times, and now Tristan gets to flip the script and interview Eric. Eric is a journalist veteran, covering everything from finance to the Boston Red Sox, but now he spends a lot of time with vendors in the data space and has a broad view of what's going on. Eric and Tristan discuss AI and analytics and how mature these features really are today, data quality and its importance, the AI strategies of Snowflake and Databricks, and a lot more. Plus, part way through you can hear Tristan reacting to a mild earthquake that hit the East Coast.

    For full show notes and to read 6+ years of back issues of the podcast's companion newsletter, head to https://roundup.getdbt.com.

    38 min
  • Being Pro-Human in the AI Era

    Barry McCardel is the co-founder and CEO of Hex. Hex is an analytics tool that's structured around a notebook experience, but as you'll hear in the episode, goes well beyond the traditional notebook.

    We're big fans of Hex at dbt Labs, and use it for a bunch of our internal data work. In this episode, Barry and Tristan discuss notebooks and data analysis, before zooming out to discuss the hype cycle of data science, how AI is different, the experience of building AI products, and how AI will impact data practitioners.

    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.

    51 min
  • The 2024 Machine Learning, AI & Data Landscape (w/ Matt Turck)

    Matt Turck has been publishing his ecosystem map since 2012. It was first called the Big Data Landscape. Now it's the Machine Learning, AI & Data (MAD) Landscape.

    The 2024 MAD Landscape includes 2,011(!) logos, which Matt attributes first a data infrastructure cycle and now an ML/AI cycle. As Matt writes, "Those two waves are intimately related. A core idea of the MAD Landscape every year has been to show the symbiotic relationship between data infrastructure, analytics/BI, ML/AI, and applications."

    Matt and Tristan discuss themes in Matt's post: generative AI's impact on data analytics, the modern AI stack compared to the modern data stack, and Databricks vs. Snowflake (plus Microsoft Fabric).

    For full show notes and to read 7+ 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.

    37 min
  • How the Media Covers Gen AI (w/ Matthew Lynley, Supervised)

    Matthew Lynley is a bit of a hybrid. He's been a long-time journalist covering enterprise tech, currently in his fantastic AI and data newsletter Supervised, and he's also been a hands-on data practitioner.

    Matthew has covered the analytics tech stack, but this time Tristan turns the tables to get Matthew's perspective on the rise of Gen AI as a topic in the popular press, what's going on in the space today, and where AI is headed.

    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.

    49 min

About The Analytics Engineering Podcast

From the publisher's feed

The Analytics Engineering Podcast goes deep with the practitioners and builders leading the shift in how data work gets done.

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