When I started my journey as a data analyst, I thought that coding was the key to everything. SQL, Python, complex functions in Excel—I believed if I could just master these, I'd be set.

Turns out, I was wrong.

The biggest breakthroughs I've had didn't come from knowing the perfect line of code.

They came from my natural curiosity, from asking what others might call 'stupid' questions, and from not being afraid to say, "I don't understand. Can we go over this again?"(as many times as needed, so my brain can map it all out).

I remember, my curiosity led me to a critical discovery about our app's performance.

I decided to look at a breakdown nobody had ever looked at before. I asked myself, "What if I also look at the data sliced by device and operating system?". That's when I found that our app wasn't working properly on a specific OS on a specific device. The session time for those users was always 2-3 seconds, and it turned out that 60% of our customers in a specific country were all using that phone model. This insight was a game changer, and it all came from the simple question: "What if I also look at data sliced by...?"

Sometimes, the value you bring isn't in the fanciest model you can build, but in the questions you ask that others overlook.

Curiosity, in my experience, is what separates a good analyst from a great one. The willingness to stay curious, to ask questions that don't come with easy answers, and to explore beyond the dataset is what leads to impactful insights.

This mindset of "what if..." not only helps find hidden issues but also helps you learn new formulas and tricks along the way. Every new insight, every new technique I've learned, has come from asking, "What if...?"

Takeaway: As data analysts, we often think we need to have all the answers. But sometimes, it's more important to have the right questions.

Remember:

• SQL can tell you WHAT happened

• Python can tell you WHEN it happened

• But only questions can tell you WHY

Don't be afraid to ask the obvious, to question assumptions and to say, "I don't know."

The best insights don't come from the fanciest analysis. They come from being the person who's brave enough to ask the obvious questions.

Keep pushing 💪

Karina

Excel Tip

I came across a formula that can be used as an alternative to LOOKUPs and INDEX+MATCH:

DGET(database, field, criteria)

In the example below, we have a database (Table A1:D5 ) that contains a list of items and sales broken down by month.

In cell G3, we want to get the sales value for "Dress" in "Feb." The formula will look like this:

=DGET(A1:D5, G2, F2:F3)

Where:

• A1:D5 is our table

• G2 is the field (month)

• F2:F3 is the criteria.

The formula is dynamic, so if you change the value in F3 (e.g., from "Dress" to "Pants") or the value in G2 (e.g., from "Feb" to "Mar"), the number will be recalculated.

ChatGPT Prompt

If you’ve been using chatGPT for some time, it’s added some knowledge about you to its memory. Try this prompt:

based on what you know about me, draw a picture of what you think my life looks like 

This is what ChatGPT thinks my life looks like:

Grab your freebies if you haven’t done already:
Data Storytelling Guide

Data Playbook (CV template, Books on Data Analytics and Data Science, Examples of portfolio projects)

Need more help?

Just starting with Python? Wondering if programming is for you?

Master key data analysis tasks like cleaning, filtering, pivot and grouping data using Pandas, and learn how to present your insights visually with Matplotlib with ‘Data Analysis with Python’ masterclass.

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