Tuesday, 9 May 2023
Full-time fun - why join an early stage startup
9 days into May, and I feel like I have a bit of an "announcement" to share that has been a few months in the making.
End of last year, I came to the end of a long (10,5 years!) and rewarding journey at Neo4j. I had put my heart and soul into that project, and was at the same time sad and thankful for the goodbyes that I had to say. Lars Nordwall and Emil Eifrem will forever be in my heart, as will be so many other wonderful graphistas that I got to know and love.
At the end of a journey like that, you would think that you want want to take it easy, or take your time, or do nothing for a while. And in some ways I did. But in other ways, I just did not want too much idle time. Having some time to reflect would be good. Having too much time to reflect would have someone like me go pretty crazy, pretty fast.
So when Pascal Desmarets and I had a wonderful lunch sometime in January, I decided pretty quickly that I was not going to let the opportunity pass, and that I would want to do some part time work for Hackolade. It seemed like a great idea - and now, 3+ months later, I feel like it really was. Earlier this month, on May 1st, I joined the Hackolade team as full time member - and I could not be more stoked about that. Let me tell you why I feel that way.
Labels:
career,
data governance,
data modeling,
hackolade,
nosql,
startup
Thursday, 4 May 2023
Size does matter, also in Data Modeling!
Recently, my colleague Pascal Desmarets wrote a fantastic article about “Domain Driven Data Modeling”. Many things I liked about that article – especially how Pascal was able to tie together some of the best insights that I know of in Agile software development methodologies, with the best practices in modern Data Modeling practices. The two are clearly linked: if you truly want to implement an agile development methodology, then you need to have data models that follow the principles of that methodology. The reason for that should be obvious: development concerns are some of the core concerns that we try to address with modern data modeling tools.
In the article, Pascal maps the core principles of one of the great, proven agile software development methodologies (Domain Driven Design) onto the practice of data modeling:
No surprise: these principles are at the core of the Hackolade toolset that we have now spent years developing.
As you will see, Domain Driven Data Modeling has some inherent comments that pertain to the SIZE of a data model. This is one of the core points that Pascal tackles in the early part of his article, and a really interesting one to me.
In the article, Pascal maps the core principles of one of the great, proven agile software development methodologies (Domain Driven Design) onto the practice of data modeling:
No surprise: these principles are at the core of the Hackolade toolset that we have now spent years developing.
As you will see, Domain Driven Data Modeling has some inherent comments that pertain to the SIZE of a data model. This is one of the core points that Pascal tackles in the early part of his article, and a really interesting one to me.
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