14 thoughts on the economics of the open-source data space and how to become the next MongoDB or Databricks — The data space is booming, with companies like mongoDB (valued at 18 billion USD), databricks (30 billion), or Confluent, and many others. The startup space is overflowing with money and lots of founders want a share of the pie. But in my opinion, the data space is set up to…

Fast Prototyping techniques NocoDB, Git, Terraform, Qwik and OpenBook used to prototype massively successful open source projects. — “The vast majority of times I meet a team […] They have spent literally months building an [prototype] when they could’ve had this same learning in days, or even in hours.” (Marty Kagan, “Inspired — How to create tech products customer love”) Think this doesn’t apply to open source projects…

If you ever get bored of mediums’ data content, these places are where you’ll get the exciting stuff. — Nowadays data content is everywhere, medium, Twitter or substack. If you want to know what the accepted knowledge is, you should continue to read all of these. But if you want to know what the topics of tomorrow are, you need to step outside. Zhamak Dehghani did not publish her…

Barr Moses 7 predictions for data engineering in 2023 are spot on, they support the underlying trends that will last much longer! Tx Zhuo already talked about the major shifts happening now back in 2016. The State of IoT is still doing good even though growth has slowed down to 8% and supports the underlying forces of data. — This usually goes into my private Three Data Point Thursday newsletter, but I thought predictions for 2023 are always nice to share in the open! Enjoy.

A Data Mesh for data-heavy-product companies. — Finding a good technical architecture for a data mesh is hard and a very company-specific process. Kafka-based data meshes are a great choice for companies that build data-heavy products already. If your software engineers won’t be comfortable processing heavy amounts of data, and are not able to get into the…

The four skills that make great web3 founders also make great data founders: unlearning, pie making, systems thinking & community leading — Web3 founders work their products & early start-ups very differently than others, and data founders should too. The data space is becoming increasingly complex and adopts more and more openness, just as much as with open-source, as they do with user communities. In some parts, 50–80% of start-ups bet on…

How to write policies that are automatable, implement them and grow your rate of computational governance as your company matures — In this article, I’ll explain a simple framework that will help you working on the “computational” parts of your data governance inside a Data Mesh. We will: Explain what “computational” means, but do not cover “federated computational governance” in all details. …

Reverse ETL is just another buzzword, and yet the idea behind it has been a game changer for me as a data engineer & data product manager for making users more data-driven. Reverse ETL means taking data from your centralized data warehouse or data lake and pushing it out into…