Why Most Data Career Advice Is Written for People Who Don't Need It
Learn SQL, build a portfolio, contribute to open source. The canonical data career advice is optimised for getting your first job, and useless immediately after.
Tutorials, opinions, and tricks for people who live in the Microsoft stack — and want to stop fighting the software they're already paying for.
I'm Bianca — a citizen developer who helps people who live in Excel, Word, and PowerPoint make the Microsoft tools they already pay for actually work for them. I'm open to work.
Learn SQL, build a portfolio, contribute to open source. The canonical data career advice is optimised for getting your first job, and useless immediately after.
Joining a column of names or tags into one comma-separated string used to need TEXTJOIN or a helper column. REDUCE does it in one formula, and lets you transform each item before it gets concatenated.
The title changes, the salary changes, and the list of skills that matter changes completely. Worse, the things that made you good as an analyst quietly start working against you at the senior level.
Most introductions to star schema start with the diagram. The star, the centre, the spokes. This one starts with the question: what problem does a fact table solve that a flat table doesn't? Part 1 builds the intuition before the vocabulary, so the rest of the series makes immediate sense.
LAMBDA, MAP, REDUCE, SCAN, BYROW. These are functional programming primitives. Excel is shipping them one by one, and most users are still writing nested IFs. The spreadsheet you learned in 2015 has been quietly replaced by something much more powerful.
You'll build a dropdown list that reads from a structured table and includes every new row automatically. No named range maintenance, no 'why isn't my new entry showing up' moments. Structured table plus a spill reference, and your validation list never needs touching again.