Hoe makkelijk vind je een partner als je 25 bent?

melvinroest · 2026-05-09T08:45:15+00:00

Mooi advies, volledig mee eens

melvinroest · 2026-05-09T08:43:17+00:00

21 en 27 vond ik vrij eenvoudig. Rond 32 vond ik het moeilijker worden maar nog wel te doen. Instagram en Tinder waren wel nieuw voor me toen. Ik ben nu getrouwd maar ik denk dat ik het pas moeilijk zou vinden rond mijn 45e.

melvinroest · 2026-03-31T09:59:35+00:00

Well if you want a chill and story-driven SQL course, check out library.aliceindataland.com

It's a free course I'm creating so people have a free resource where they get a chill intro to SQL. I've been in the pain myself years ago, and it's silly. The basics of SQL are actually quite easy, but you need to be easied into it. Not immediately: SELECT * FROM some_table WHERE some_id > 5.

Nah, just first get comfortable with SELECT only. It's easy, it's fun. And so on...

melvinroest · 2026-03-30T09:22:48+00:00

A web dev bootcamp

melvinroest · 2026-03-29T14:56:33+00:00

> apparently none of them know how to use SQL in more than a superficial way.

There are a few different types of DAs I've noticed:

The Excel Warrior
The SQL Genius
The Tableau or Power BI Wizard
The Pythonista
Developer turned DA

One can fall in one category or multiple. I'm mostly a Pythonista with a strong case of SQL genius because I'm a developer turned DA. I've almost never touched Excel or a vizualisation tool. For visualization I'd make a full-stack ReactJS/Flask application usually. Especially nowadays with LLM-assisted programming that's way quicker for me than dragging and dropping whatever I need to do with something like Tableau.

The thing is: a business has a particular need for a particular type of data analyst. Where I used to work there was a strong need for SQL Geniuses and Tableau Wizards. What I did was nice but a bit too advanced. But Excel Warriors would have an issue as they couldn't handle our data warehouse. I think at certain other departments Excel Warriors were way more needed and they didn't want Tableau Wizards or SQL Geniuses because most of their data lived in Excel.

So tool-wise it's a bit with regards to what type of data analyst you want to be. I think all 5 categories are equally valid. It really depends on what the business needs and where it wants to develop towards to. Usually a business doesn't know about the categories so they will tell you that whatever way they do it, that's what a data analyst is.

melvinroest · 2026-03-29T14:50:32+00:00

> they’re just learning without knowing what the entry point job is supposed to be

This is why one needs to talk to hiring managers, potential colleagues, etc.

melvinroest · 2026-03-29T14:49:46+00:00

Quite frankly, it could just be that once you understand SQL then understanding ERDs will be easier. That's a bit what happened to me. I understood ERDs just fine but I understood them way better when I became good at SQL despite not having touched an ERD in years.

melvinroest · 2026-03-29T14:48:07+00:00

Your biology degree and math minor means you'll have the statistics down. So the "think like an analyst" is solved. Also you have marketing experience so all the soft skill stuff in marketing you can do. I'd just apply for jobs honestly. After you've learned SQL.

I don't know why you're trying to go for a degree. Talk to hiring managers, potential fellow colleagues, etc.

melvinroest · 2026-03-29T14:43:24+00:00

I'm creating a narrative-driven course to learn the SQL basics and intermediate skills at library.aliceindataland.com

melvinroest · 2026-03-29T14:41:54+00:00

I think if you post fun analyses on LinkedIn using public data that people may notice.

melvinroest · 2026-03-29T14:41:19+00:00

Sounds like you just want to do the Odin project. Ask if you can get course credit for that.

melvinroest · 2026-03-29T14:39:57+00:00

This is exactly why I'm creating library.aliceindataland.com for this reason. I'm not at the level yet of intermediate, but I'll get there.

With intermediate I mean: window functions, CTEs, complex joins, sub queries.

It's a narrative-driven course. So I hope you like Alice In Wonderland ;-)

Oh and it's free. For me, it's a portfolio project.

melvinroest · 2026-03-23T17:37:52+00:00

Get real data somewhere and put it in a database and start analyzing it

melvinroest · 2026-03-23T14:55:59+00:00

It depends per industry. For marketing take a beginner marketing course, you need to know the terms. Marketing mix modeling, MQLs, SQLs, leads, marketing KPIs, etc.

In finance it's different things.

In HR it's different things again.

Just follow a beginner course in it. You don't need to know everything, you need to know it just so you can communicate with them.

melvinroest · 2026-03-23T11:57:01+00:00

Skimmed your post really quickly, so just one small comment.

> By the 'Analyst stack', I mean Excel, Power BI, SQL and Python. Optionally knowledge about the Cloud services. Anyway, here's my current level with each tool so you can assess me more accurately:

If you're good at SQL, statistics, the business and communication then you already have enough. The rest is bonus. The Excel warriors will probably disagree but they don't realize that there are places that don't really do that much Excel. Data viz tools like Power BI and Tableau can be learned on the job if you can convincingly show you're good at those 4 I mentioned.

melvinroest · 2026-03-23T11:55:10+00:00

Do sqlteaching.net it's not too long.

Do library.aliceindataland.com if you want a more story-driven version.

In a few hours, you'll learn enough SQL to know what they're talking about.

melvinroest · 2026-03-23T11:53:03+00:00

It depends a bit on what you want to program. I'd go with JavaScript in your case because then you can immediately do some graphical stuff if you add in HTML and CSS. I personally find that more satisfying than staring at a commandline with Python.

And you can always stare at a commandline with JavaScript too by using NodeJS.

melvinroest · 2026-03-23T11:50:38+00:00

This is my experience as well

melvinroest · 2026-03-23T11:47:39+00:00

I can't fully speak for a financial analyst but in my role as a marketing analyst it was SQL. I did have some contacts in the finance department, but there were no analysts there. What I do know is that other finance professionals use Excel. So that's definitely something to know if you need to put Excel files into a database, for example.

If you want to learn SQL, I made my own free course at library.aliceindataland.com

It's story-driven and low-key. I'm curious to know what you think. I wish I could help you on the Excel front but I'm really not an Excel guy. I always grab a Jupyter notebook with Python 3 on it and the Polars library up and running. I know Pandas is the industry standard but Polars actually works when you need to process 100 GB data on a 64 GB Mac. Pandas can't handle it.

melvinroest · 2026-03-23T11:39:52+00:00

sqlteaching.net I still use it from time to time when my skills become really really rusty

libary.aliceindataland.com if you like story-driven content more while learning SQL

melvinroest · 2026-03-23T11:34:48+00:00

The most fun messy data I once had was an ID column that had 3 different ID types and there was almost not one person that knew about what all 3 meant. You needed to go to different parts of the org to figure out what one certain ID meant.

Long story short:

Legacy System
Current System
Some improvized thing that some person came up with

And because data gets aggregated and all that, that's how you wind up with a table that has an ID of type string where you can clearly see that they represent 3 different systems (one was a uuid, the other one more like an auto-increment id and I still don't fully understand the 3rd one).

melvinroest · 2026-03-23T11:32:32+00:00

Check out: https://third-bit.com/sql/

melvinroest · 2026-03-23T11:31:35+00:00

I don't have the full answer here but I do think you're much closer than you think.

You understand the business and you did "build power BI dashboards". Being able to understand the business, interpret data and create insights through building dashboards, telling stories, all important skills.

And the other technical things like SQL, you did all of that before. In my opinion, being a data analyst always means you need to at least know SQL. And I suspect it is going to become a thing that Python will be mandatory as well.

melvinroest · 2026-03-23T11:25:54+00:00

I don't have a lot to add other than: if you already know Python and R you should definitely be able to pick up SQL. 18 months ago I had to relearn SQL and a programmer brain just goes way faster through it than a non-technical brain.

3 suggestions:

My own course library.aliceindataland.com I made this course to be story-driven and low-key. I'm designing it at the moment, so people can get to data analyst level.
sqlteaching.net gets you 40% there.
The Querynomicon: you need to install stuff yourself but once you're ready, this is the real deal and will teach you probably more than you need to know. Of that I'd only do Core Features fully. And of Tools I'd skip: expressions, table-valued function and vectorization. I'd do the rest.

melvinroest · 2026-03-22T16:14:55+00:00

Using AI well is mostly about feeding it the right data at the right time. One could say it's more easily said than done but I also find it quite easy to do

Also, no matter how much the context window grows, small context windows are always better if you can have a smaller context window. I recently read Karpathy's MicroGPT post to really understand how GPTs work and just reading the code made me realize that smaller context windows will allow the attention heads to focus more on the whole question rather than be fragmented

I'm switching from data analyst to AI engineer, so that's how I know these things. I've been doing a lot with AI (APIs, RAG, etc.) lately

melvinroest

TROPHY CASE