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…

Build your data company faster, manage your data products better, and invest smarter by using data-specific mental models — “In Munger’s view, it is better to be worldly wise than to spend lots of time working with a single model that is precisely wrong. A multiple-model approach that is only approximately right will produce a far better outcome in anything that involves people or a social system.” …

5 Reasons to switch your career to data product management. — I’ve noticed a shift. It happened to me when I entered my role as data PM, it is happening all around the tech industry. It is happening in traditional industries, and it comes fast. Data product management, emphasis on data, is becoming a thing. In job titles, web content, discussions…

7 Lessons to build lean, simple, and agile data stacks, not fat ones. — Data architecture, it’s that time of the year again. For some reason, whenever it is dark outside, so are the thoughts about your own data architecture, outdated, too complex, something is missing. But it doesn’t have to be that way. The solution is not to hire dedicated data architects that…

What Writing a PhD Thesis In Singularity Theory Has Taught Me About Data Engineering — In August 2017 I started writing my phD thesis in a field called singularity theory. Not the fun AI kind of theory, but the mathematical version about “when unexpected things happen”. And so it happened, that while I was still sitting more in my office than actually writing, a friend…

The two types of user conversations that I still get sucked into — Starting out inside a data team years ago, maturing into a data product manager role, and even today, I catch myself slipping into the same type of conversations with end users. One that sets me up for failure. The big mistakes I make is to: assuming a solution. focus on…

31 “Simple” Steps to Build A COSS Company — “Software might be eating up the world, but open source is eating up software faster!” GitLab is now a commercial open source software (COSS) giant. The DevOps tooling company has a market cap of roughly 7 billion USD and 400 million in revenue. …

Learn these skills to stand out as a mature data engineer. Once you’ve mastered the basics of data engineering, this is how you advance and stand out. — Beginning in January, Amazon started to lay off data scientists and other engineers. Amazon follows Twitter, Netflix and many others of the tech giants flooding the market with data-related talent. A lot of these people target a wide array of possible positions, from data science to data engineering.

Three inspiring chaos experiments to help any data team make their stacks more resilient — Ever randomly deleted instances, running containers, databases inside your production system? Some time around 2008, a crazy or rather brilliant engineer around Netflix started to randomly delete ec2 instances of engineering teams in the production system. Why on gods earth would he do that? Turns out, he was teaching teams…