By this time of the year, the yearly plans that everyone worked so hard on in December are, best case, getting revised, and worse case, already out the window.

In all the organizational reshuffling, one of the questions that often comes up is how to evolve the data team. Should it be a central data team? Should it be completely decentralized?

More than an answer, I want to share the philosophy that Zhamak Dehghani makes the case for in her post about Data Mesh Principles and Logical Architecture.

Data mesh argues that the ownership and serving of the analytical data should respect these [business or product] domains. For example, the teams who manage ‘podcasts’, while providing APIs for releasing podcasts, should also be responsible for providing historical data that represents ‘released podcasts’ over time with other facts such as ‘listenership’ over time.

Does it mean that product dev teams should be responsible for the analytical data of their products? Does that imply being responsible for serving that data via an API? What type of platform would they need? 🤔

What’s new?

We’ve been hard at work and we’re excited to share our latest product updates.

❄️ Open signups for Snowflake customers: If you need to build analytics for your customer-facing product, you can now power it with your Snowflake data. Customers have built what are typically multi-month projects in a couple of weeks with just Snowflake + Propel + and their front-end engineers. You can get started now.

🏗️  Propel Terraform provider: We’re big believers and practitioners of infrastructure as code. That’s why we’re so excited to launch the Propel Terraform provider. It allows you to define your Propel configuration in code, including Data Sources, Data Pools, and Metrics, source control it to track changes, and have repeatable deploys across environments. For more details, read the blog post.

📊 Propel’s Grafana plugin: An easy way to have internal observability for your Propel data. While Propel primarily powers customer-facing use cases, internal observability gives you peace of mind when operating your customer-facing products. You can leverage Grafana’s powerful visualization features to monitor the data you are serving to customers. For more details, read the blog post.

Lastly, check out all the improvements and fixes in our changelog.

The latest posts and episodes

From Propel

Snowflake Startup Spotlight: APIs on Top of Snowflake with Propel  @ Snowflake Blog  — Nico Acosta, CEO at Propel

In Snowflake’s blog, Nico writes about how Propel is building an API platform to equip developers to build with data, and why data architecture is the most important technical decision a company will make.

What is the Data Chaos Podcast? — Tyler Wells, CTO at Propel

Listen to the trailer of our new podcast, Data Chaos, a deep dive focusing on the people, technologies, and all things surrounding the journey of data in today's companies. Subscribe on Spotify or Apple Podcasts.

Universal truth - All JSON will need to be transformed — Tyler Wells, CTO at Propel

In this thread, Tyler talks about handling JSON payloads in the real world and small details that end up requiring in-flight JSON transformations.

From the community

Tools and Techniques to Establish Your Data Team Early — Raymond See, Head of Data at Courier

If you’re an early-stage startup, this is a must-read. Raymond shares how they started thinking about their data strategy, team, and architecture early on without going too big, but with the ability to have a big impact.

How to get started with Propel?

Easy peasy. Sign up for a free account and start building 👩🏽‍💻  🏗️  🚀!

Thank you for reading!