
Practical tips around Data Analytics, Analytics Engineering and Modeling from a former Marketing Analyst who transitioned into a Full-Stack Data Worker. 10 year experience in various industries, data stacks and business domains across Start- and Scale Ups
| Platform | Pricing | Only free issues | Publishes | Weekly | |
|---|---|---|---|---|---|
| Issues | 31 | Founded | a year ago | Last Issue | 3 months ago |
| Active | |||||

Nowadays, I usually try to use AI for any job to figure out how well it works currently and whether it would be helpful in the future. With agentic coding on the rise and the underlying models, frameworks, and surrounding tooling getting li...
Over the past few years, I’ve noticed a fascinating trend: the worlds of software and data are colliding. This isn’t just about job titles or team structures—it’s about how we build, deploy, and integrate systems. Whether you’re an engineer...
When data transformations got simpler and “democratized”, it didn’t just change how we work. It created a whole new cohort of data practitioners.
But here’s the twist: many of these folks (including me) were unfamiliar with established d...
The recent AI hype—especially around analytics chatbots and “AI analysts”—feels like déjà vu. A decade ago, startups promised the same magic - type a question in plain English, get a SQL q...
You’ve built your data warehouse and your core reporting infrastructure.
That’s a huge win. But too often, a critical step is either missed or undervalued: Data Testing. I frequently encounter setups where teams have “not yet” added —or...
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