What tool or skill turned out to be way easier — or way harder — than you expected when you started learning it?

For a lot of people it's SQL (easier than they feared) or DAX (harder than it looks). But everyone's different.

What was yours?

We're not talking about the basics; SUMX and CALCULATE you probably already know.

These are the ones that show up constantly in real reports and take a while to find if you don't know they exist.

1. DIVIDE() instead of division

Using [Sales] / [Units] will throw an error when units is zero. DIVIDE([Sales], [Units], 0) handles it gracefully and returns 0 (or whatever you set as the alternate result). Simple swap, saves headaches.

2. SELECTEDVALUE() for single-selection slicers

When you want a measure to respond to what a user selects in a slicer — and only when exactly one thing is selected — SELECTEDVALUE() is cleaner than a FILTER/VALUES combination. It returns the selected value or a default if nothing or multiple things are selected.

3. RANKX() for dynamic rankings

If you've ever built a "top N" report that breaks when filters change, RANKX() is the fix. It recalculates rank dynamically based on whatever's in context. Combine it with a top N slicer and you have a fully dynamic leaderboard.

None of these are advanced DAX, but they're the patterns that separate reports that work from reports that sort of work.

Which DAX function took you the longest to actually understand?

Let's try something new! We're curious to see how this plays out...

Give the tools you actually use a letter grade. A through F. (Be honest!)

To get you started, here's how our team thinks about it: the grade isn't about whether the tool is good in general; it's about how it holds up in your actual day-to-day work.

Drop your grades below with a one-line explanation.

Especially interested in the Cs, Ds, and anyone bold enough to give something an F!

If you hit a wall this week, post it below!

It could be...

• a formula that won't cooperate
• a join that's returning the wrong thing
• a chart that looks off
• a concept that isn't clicking

Someone in this community may have been in the same spot. And explaining a problem out loud (or in a post) has a way of helping you solve it, too.

No question is too basic!

What's one thing you wish someone had told you before your first data job?

Not the technical stuff.

The stuff nobody mentions, like how vague the requests are, how messy real data actually is, or how much of the job is just explaining things to people who don't want to look at charts.

Drop yours below; this could save someone a lot of time!

What are you working on this week?

If you can, we'd love to see a screenshot of a dashboard, a query you finally got right, a chart you're weirdly proud of. Even a work-in-progress you want a second opinion on.

Big or small, drop it below!

This community has people at every skill level, and there's usually someone who's either been stuck in the same place or has a tip that helps.

Most people learn SELECT, WHERE, GROUP BY, and call it done. Then they hit a problem that GROUP BY can't solve — and that's usually when window functions finally click.

Here's the short version of what they do:

They let you perform calculations across a set of rows related to the current row, without collapsing the data into groups. So you can calculate a running total, rank records, or compare each row to a previous one...

...all while keeping every row intact.

The functions you'll use most often:

ROW_NUMBER() — assigns a unique rank to each row within a partition. Great for deduplication.

RANK() / DENSE_RANK() — similar, but handles ties differently. Useful for leaderboards or top-N problems.

LAG() / LEAD() — pulls a value from the previous or next row. The fastest way to do period-over-period comparisons.

SUM() / AVG() OVER() — running totals and moving averages without subqueries.

The syntax that trips people up at first is the OVER() clause — that's where you define the window. PARTITION BY works like GROUP BY (but doesn't collapse rows), and ORDER BY sets the order within each partition.

Once this clicks, you'll start seeing problems differently. A lot of things that used to require subqueries or self-joins become one clean window function.

What's your go-to window function, and what problem does it solve for you?

Big or small — share what you’re digging into!

It could be...

• A dashboard
• A course
• A portfolio project
• Job searching
• Learning Excel / SQL / Power BI / Tableau

If you’re stuck, drop it here, too. Someone will probably have a tip!

Big or small — share what you’re digging into!

It could be...

• A dashboard
• A course
• A portfolio project
• Job searching
• Learning Excel / SQL / Power BI / Tableau

If you’re stuck, drop it here, too. Someone will probably have a tip!

By default, Excel uses Compact Form report layout.

Which means:

• All your row labels get crammed into one column
• You get those weird spacer rows
• And the whole thing doesn’t look anything like a normal table

Great for quick analysis… not great if you actually want to use that data somewhere else.

Here’s the fix:

Go to the Design tab → Report Layout → Show in Tabular Form

Then:

Click “Repeat All Item Labels”

Turn off subtotals: “Do Not Show Subtotals”

Now your Pivot looks like a proper table, has clean, repeatable rows, and is actually usable for copy/paste or downstream work!

This is one of those small tweaks that makes Excel way more practical once you know it.

Anyone else have a quick Excel tip to share?

We see a lot of posts from people trying to learn data skills on their own.

Some succeed… but a lot stall out.

Not because they’re not capable. Because self-guided learning has a few built-in flaws that don’t get talked about enough.

Here are the 4 biggest ones:

1. You don’t know what you don’t know

When you’re learning solo, it’s really hard to see the full map.

So people end up:

• Over-indexing on tools (jumping from Python → SQL → Tableau → back to Python)
• Skipping fundamentals that actually matter
• Or going way too deep on niche topics too early

You’re making decisions without context, which slows everything down.

2. No feedback = slow (or wrong) progress

You can follow tutorials and feel like you’re improving…

But without feedback, it’s easy to reinforce bad habits, miss better approaches, or think you “get it” when you don’t yet.

In real data work, feedback is everything. It’s how you sharpen your thinking.

3. Motivation drops when things get hard

Early on, progress feels fast.

Then you hit messy datasets, vague problem statements, and concepts that don’t click immediately.

And suddenly, it’s just you… trying to figure it out.

That’s where most people stall.

4. No clear connection to real jobs

A lot of self-study paths focus on isolated skills, clean datasets, and perfectly scoped problems…

…But actual data roles are messy.

If you don’t practice framing problems, making decisions with imperfect data, and communicating insights, it’s hard to translate learning into a job.

Self-guided learning can work.

But it works best when you add structure:

• A clear roadmap (what to learn + in what order)
• Feedback (from mentors, peers, or instructors)
• Real-world projects
• And some form of accountability

AI is making it easier than ever to learn tools…

But the people who stand out are the ones who combine strong foundations, practical experience, and good judgment.

That part still takes intention.

For those of you learning data skills right now:

What’s been the hardest part of doing it on your own?