Elementary featured on the Data Engineering Podcast

I recently sat down with Tobias Macey, host of the Data Engineering Podcast, to talk about adding observability to your dbt project using Elementary.  
‍
In this 50-minute conversation we covered a lot of topics, including how dbt teams are adding observability and insight to their dbt projects, why Elementary is different from other data observability platforms, and how the adoption of Elementary has improved the development habits of teams using the platform.

I also get into some of our plans for the future.
‍
Check it out here:

Here is the full list of questions covered in this conversation:

• How did you get involved in the area of data management?
• Can you start by outlining what elements of observability are most relevant for dbt projects?
• What are some of the common ad-hoc/DIY methods that teams develop to acquire those insights?
• Over the past ~3 years there were numerous data observability systems/products created. What are some of the ways that the specifics of dbt workflows are not covered by those generalized tools?
• Can you describe what Elementary is and how it is designed to enhance the development and maintenance work in dbt projects?
• How is Elementary designed/implemented?
• Can you talk us through the setup and workflow for teams adopting Elementary in their dbt projects?
• How does the incorporation of Elementary change the development habits of the teams who are using it?
• What are the most interesting, innovative, or unexpected ways that you have seen Elementary used?
• What are the most interesting, unexpected, or challenging lessons that you have learned while working on Elementary?
• When is Elementary the wrong choice?
• What do you have planned for the future of Elementary?

Learn more about Elementary here.