Stop letting Reddit dictate your career.

If you want to know which skills can help you get hired, don't start with online forums. Don't ask your buddies. And honestly, don't trust every random YouTuber either.

Ask the job market.

So that's what I did. I analyzed 11,060 real data job postings from my job board, findadatajob.com, to see what companies are actually asking for.

And some of the results surprised me.

Eighteen months ago, I said Power BI would not catch Tableau. "Argue with me in the comments," I said.

Well, I was wrong. And that was not even the biggest surprise.

Here's what actually happened.

Excel is not going anywhere

Last time I did this, Excel showed up in 39% of data job posts. Now it's at 49%. That means almost 1 in 2 data jobs mention Excel.

I know Excel feels old. I know it does not feel as exciting as Python, AI, or machine learning. But companies still run on spreadsheets. Finance teams use them. Operations teams use them. Managers use them. Analysts use them too.

So if you skip Excel because it feels too basic, you might be skipping the one skill that gets you hired fastest.

Then there's SQL

SQL went from 31% to 38%. Not surprising. SQL is still the backbone of data work.

If your company stores data in a database, someone has to pull it out, clean it, filter it, join it, and make sense of it. That someone is usually the analyst.

SQL is not fancy, but it keeps showing up for a reason.

Power BI passed Tableau

Last year, Power BI was at 13 percent and Tableau was at 21 percent.

This time, Power BI jumped to 26 percent. Tableau moved up slightly to 24 percent.

So Power BI has now pulled ahead.

Why? My guess is Microsoft. A lot of companies already pay for Microsoft 365. Power BI fits into that world. And when a tool already fits how a company works, it has a big advantage.

Does this mean Tableau is dead? No. Not even close.

Tableau is still in demand, and it is still a great tool. But if you are starting today and choosing one BI tool, Power BI has a very strong case.

Then there's AI

AI and LLM skills were barely showing up before. Now they show up in 11% of data job posts.

That's already higher than tools like R, AWS, and Snowflake, tools that have been around way longer.

The good news is you do not need to become an AI engineer to start building this skill. For most analysts, AI is not about building a model from scratch.

It is about knowing how to use AI to move faster, ask better questions, explain your work, and check your results.

Python can wait a little

Python grew from 14% to 20%. R dropped from 8% to 4%.

If you're choosing between the two, the market already answered that question. Python wins for most data analyst paths.

But here's my hot take. If you're trying to land your first entry-level data job, Python probably shouldn't be your first move.

Not because Python is bad. Python is great. But it has a steeper learning curve, and the job data still shows stronger demand for Excel, SQL, and BI tools.

If I were starting over today

If I were starting today, I would keep it simple.

First, I would learn Excel. It is the most in-demand tool on the list, and it is one of the easiest to start with.

Then I would pick one BI tool, either Power BI or Tableau. Not both at the same time. Learn one well, then the other becomes much easier later.

After that, I would learn SQL. It is much easier than a full scripting language, and it shows up across almost every type of data role.

Then I would start using AI tools to speed up my work and learn how to check the output.

Only after that would I add Python.

So the path would look like this:

Excel → BI tool → SQL → AI → Python

Stop building your learning plan from what people online think is cool.

Build it from what companies are actually asking for.

If you want to check the numbers for yourself, I put the live data on a free site: dataanalystskills.com.

It updates daily, and you can filter by things like remote roles, seniority, and job type. So instead of guessing what to learn next, you can see what companies are asking for right now.

And if you want a simple, step-by-step path for learning these skills in the right order, that is what we help people do inside the Data Analytics Accelerator.