Daniel Avancini is the chief data officer and co-founder of Indicium—a fast-growing data consultancy started in Brazil.

There are a lot of data consultancies around the world, and a lot of them do great work. What has been so fascinating about Indicium’s journey is their HR model. Rather than primarily hiring experienced professionals, they decided to go hard on training. They built a talent pipeline with courses and an internal onboarding process that takes new employees from zero to 60 over a few months.

The result has been phenomenal and Indicium delivers great client outcomes, but most importantly, they're building skills for hundreds of brand new data professionals.

Data is a hard field to break into because fundamentally you can't do the real thing unless you have access to data. So any company that is investing in building scalable hiring and training processes for analytical talent is one to be excited about.

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.

A look inside at the data work happening at a company making some of the most advanced technologies in the industry. Rahul Jain, data engineering manager at Snowflake, joins Tristan to discuss Iceberg, streaming, and all things Snowflake.

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.

Hamilton Ulmer is working at the intersection of UI, Exploratory Data Analysis, and SQL at MotherDuck, and he's built a long career in EDA. Hamilton and Tristan dive deep into the history of exploratory data analysis. Even if you spend most of your time below the frontend layer of the stack, it is important to understand the trends in both the practice of data visualization and the technologies that underlie that practice.

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.

Fivetran recently passed $300 million ARR and has over 7,000 customers globally. Taylor Brown, the cofounder and COO of Fivetran, joins the show to talk about Fivetran’s moat, the impact of AI on the data ingestion space, and open table formats and catalogs.

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.

Cedric Chin runs Commoncog—a publication about accelerating business expertise. He joins Tristan to talk about the analytics development lifecycle, how organizations value (or misvalue) data, and why “data teams are not some IT helpdesk to be ignored.”

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.

Erik Bernhardsson, the CEO and co-founder of Modal Labs, joins Tristan to talk about Gen AI, the lack of GPUs, the future of cloud computing, and egress fees. They also discuss whether the job title of data engineer is something we should want more or less of in the future. Erik’s not afraid of a spicy take, so this is a fun one.

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.

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.

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.