Stop "tutorial hell!”

The data world is noisier than ever. Between “AI taking our jobs” and a million new essential tools, it’s easy to feel like you’re falling behind.

But here’s the truth: The fundamentals haven’t changed.

The tools have just gotten better, and the expectations have gotten higher.

Companies don’t want someone who can just run a query; they want someone who can translate messy data into a business win.

I’ve spent years working in data analytics, and I’ve seen what actually makes a difference.

This is my hand-picked list of the best resources to help you skip the confusion and start building your competitive edge.

P.S.: If this helps you, hit the share button. Let’s get more people building cool things with data.

1. The Core Foundations (The All-Rounders)

Before you touch complex AI, you need a solid understanding of data.

These are a few platforms where I recommend everyone starts. Pick one and learn all you can:

• Maven Analytics — My top recommendation for “business-first” analytics. Maven is different because they don’t just teach you the code; they teach you how to think like a consultant. Their courses on Excel, Power BI, and Tableau are industry-leading. If you want a portfolio that actually gets you hired, their guided projects are the gold standard.

  P.S. Use code DATAWITHSARAH at checkout for 20% off all plans!

• DataCamp — Perfect for practicing your skills. Their interactive, in-browser labs mean you can practice SQL and Python without the headache of setting up a local environment. It’s the best way to get those first 100 hours of coding under your belt.

2. Mastering the Language of Data: SQL

SQL is the one skill that is truly non-negotiable. If you can’t talk to a database, you aren’t ready to enter the field.

• LearnSQL.com — If you want to move beyond SELECT *, this is the place. They have the most comprehensive SQL tracks I’ve found, covering everything from basic reporting to complex recursive queries and window functions. It is pure, concentrated SQL mastery.

3. The “Big Tech” Credentials

When you want the certifications from the tech giants, themselves, go straight to the source.

• Microsoft Learn (Power BI & Fabric): If you’re serious about the Microsoft ecosystem, you need to be here. I highly recommend the PL-300: Power BI Data Analyst Associate path. It’s rigorous, but it’s the credential that corporate recruiters look for first.

• Google Learn (Google Cloud & Analytics): The Google Data Analytics Professional Certificate is still the #1 entry point for most people. But for 2026, keep an eye on their Google Cloud Data Analytics path—learning how to handle data in the cloud (BigQuery, Looker) is where the high-paying roles are moving.

4. The Toolkit: Timeless Books & Strategy

Tools change but data strategy is forever. These are the books I keep on my desk.

• Storytelling with Data — Stop making ugly charts. This book teaches you how to strip away the clutter and make your insights impossible to ignore.

• Naked Statistics — The most un-boring math book you will ever read. It explains the “why” behind the numbers without making your eyes glaze over.

My 2026 Strategy for Success

If I were starting from scratch today, here is my 6-month roadmap:

1. Month 1: Knock out the Google Data Analytics Certificate to get the big-picture view. Use this as a way to get a feel for data and if the path is right for you.

2. Month 2: Go all-in on SQL with LearnSQL.com. Don’t stop until window functions feel like second nature.

3. Month 3: Pick a BI tool (Power BI or Tableau are my top recs) and master it via Maven Analytics or DataCamp.

4. Month 4: Build three high-quality projects using real-world data (not the Titanic dataset!).

5. Month 5: Start sharing your insights on LinkedIn and Substack.

6. Month 6: Optimize your LinkedIn, tailor your resume for "Senior Analyst" or niche roles, and start applying. Treat the job hunt like a data project itself, and track your conversion rates!

If you found this list valuable, I’d love for you to share it with your network!

Share

Disclaimer: This post contains affiliate links. If you sign up through them, I may earn a commission at no extra cost to you. I only recommend tools I use and trust.

Four hundred lines.

You know the kind.

Nested subqueries, no aliases… oh my!

And it reminded me of something I see with a lot of analysts.

They want to become a Senior Analyst, but they are still doing junior work.

And it has nothing to do with skill. They have the skill.

But they are stuck doing maintenance. They are not improving anything or being proactive.

Instead, they are:

• Cleaning the same dataset every week.

• Fixing the same Excel sheet again.

• Explaining the same dashboard to the same stakeholder for the tenth time.

That is not senior work.

That is being the data janitor.

A lot of people think the next step in their career is learning another tool.

• More Python.

• Another certificate.

• Another course.

But that’s not the whole story.

The real change is when you stop thinking about answers and start thinking about systems.

Let me explain with an example…

Most analysts can write a JOIN.

But not all of them will ask:

“Is this query going to be expensive every time it runs?”

Or

“Is there a cleaner way to structure this?”

Once your work starts feeding dashboards or models, that stuff matters a lot.

The analysts who move up fastest usually get comfortable with things like:

• Window functions for trends and comparisons.
• CTEs so queries stay readable instead of turning into a mess.
• Query performance so dashboards do not take 20 seconds to load.

You stop being the person pulling numbers.

You become the person who builds how the numbers are produced.

If that is something you want to get better at, one platform I often point people to is DataCamp.

The nice part is you can learn something and immediately try it. Their annual plans are currently 50 percent off if you were planning to study this year anyway.

Also…

If you use DATAWITHSARAH at checkout on Maven Analytics, you can get 20 percent off their plans.

So learn what you need and start applying those things to your work, and be a builder, not just someone who does what is asked.

New blog post coming later this week, so keep an eye on your inbox!

Till next time,

— Sarah

Looking for Data Analytics Resources?

You’ll find them here:

📚 You Might Also Like...

Here are a few more blog posts you might be interested in:

• 30 Interview Questions to Prepare for Your Next Data Analyst Role

• SQL Best Practices for Writing Clean, Reliable Queries

• Learning New Data Skills While Working Full-Time: How to Make It Work

• Building a Data Analytics Portfolio: What to Include and Where to Start

• You Don’t Have to Be a Math Wizard to Work in Data Analytics

Data With Sarah

Build confidence in data analytics, with clear tips, tools, and lessons that help you grow your career.

By Sarah Rajani

Let’s be LinkedIn buddies!

Want more data stuff between newsletters? I’m always on LinkedIn. Connect or follow me! I’m probably on there posting about something right now…

☕ Want to Support My Work?

If something I wrote helped you out, made you laugh, or saved you from rewriting the same SQL query five times… and you feel like sending a coffee my way, here’s where you can do that.

Totally optional. Always appreciated. :)

If you’re looking for more tips like this, I share regularly on my socials. Come and say hi 👋:
LinkedIn | Medium | Facebook | X (Twitter) | Instagram | Pinterest

Thanks for reading!

—Sarah

Note: This post includes affiliate links, which help support my work.

✨If you’re on Instagram, I have a new page.

Come follow me.✨

Hey and happy New Year 👋

I feel like I blinked and suddenly it was 2026.

January always does this weird thing where time moves painfully slow but the holidays still feel five minutes ago.

If you managed to get some real downtime in December, I hope you soaked it up. Even if you were still working, December has a way of forcing at least a small pause, and we all need that reset once in a while.

I am officially back in content mode now, so I wanted to ease into the year by sharing a few things you might find useful.

Thinking about a data course this year?

If learning or leveling up data skills is on your 2026 list, this is a good window. DataCamp is running a New Year sale with 50 percent off for January. If you have been circling it for months and never pulling the trigger, this is probably your sign.

DataCamp >

Where I am posting lately

LinkedIn is still my main home base, short posts, quick lessons, mildly unhinged Excel opinions. But I am slowly branching out and posting more consistently in other places too.

If you hang out on any of these platforms and want more data related content, feel free to follow along.

• LinkedIn

• Instagram

• Facebook

• Substack

• Medium

• Pinterest

• X

No pressure to follow everywhere.

Don’t miss this!

I’m creating more data analytics resources, but I do have a few guides already available. Check them out and grab yours today. Use the code NEWYEARNEWME at checkout to get 30% off of any of the resources, only until Jan 16!

• SQL Dialect Cheat Sheet

• Dashboard Scoping Toolkit

• SQL Best Practices

• Excel Toolkit for Data Analysts

Till next time,

— Sarah

📚 You Might Also Like...

Here are a few more blog posts you might be interested in:

• 30 Interview Questions to Prepare for Your Next Data Analyst Role

• SQL Best Practices for Writing Clean, Reliable Queries

• Learning New Data Skills While Working Full-Time: How to Make It Work

• Building a Data Analytics Portfolio: What to Include and Where to Start

• You Don’t Have to Be a Math Wizard to Work in Data Analytics

Data With Sarah

Build confidence in data analytics, with clear tips, tools, and lessons that help you grow your career.

By Sarah Rajani

☕ Want to Support My Work?

If something I wrote helped you out, made you laugh, or saved you from rewriting the same SQL query five times… and you feel like sending a coffee my way, here’s where you can do that.

Totally optional. Always appreciated. :)

Note: This post includes affiliate links, which help support my work.

And I’m excited, I’m not gonna lie!

The best part is that this stretch of November is that it’s basically data-learning season.

Canada had Thanksgiving weeks ago, but I still treat the American version as a reminder to renew the tools I actually use and drop the ones collecting dust.

And this week always has the best prices.

Black Friday week!

So I wanted to share what I’m grabbing and why it might help you too.

I keep coming back to two platforms over and over again:

LearnSQL and DataCamp.

They both have deals right now, and if you are thinking about investing in your skills, this is probably the least painful time to do it.

In case you haven’t tried them, here’s what they’re all about:

1. LearnSQL

If SQL is on your list or you want to advance your skills, LearnSQL is the best place for that.

They only teach SQL, which means the content is sharp and focused.

You get full paths for absolute beginners all the way to advanced users, and they cover SQL Server, Postgres, MySQL, and the fun stuff like window functions and recursive queries.

LearnSQL >

2. DataCamp

You have probably seen DataCamp mentioned before.

They teach everything under the sun.

The last thing I did with them was their PL-300 prep, and it helped me pass my exam the first time.

They have full data tracks, projects, and courses on SQL, Python, Power BI, Excel, Tableau, and a whole list of other things you can’t learn in one weekend.

DataCamp >

If you are starting fresh, pick SQL first. It is the easiest to use and the most useful technical tool to learn right away.

If you already know your way around queries, you can move into Python or try a BI tool.

If you are in that phase where you want to grow but cannot decide what to learn next, try out a few topics and see which one you actually enjoy.

A few good options if you need a nudge:

• A to Z SQL

• SQL Practice

• Advanced SQL

• Window Functions Practice

• Data Analyst in Power BI

• Tableau Fundamentals

• Data Analyst in Python

• PL-300 Exam Prep

These discounts disappear fast, so if you want to grab one, this is a good week for it.

If you start something new, add a comment to this post and tell me what you picked. I love seeing what people are learning and it helps me plan what to write about next.

Sending you good vibes and a very happy Thanksgiving if you are celebrating!

Till next time,
Sarah

If you’re looking for more tips like this, I share regularly on my socials. Come and say hi 👋:
LinkedIn | Medium | Facebook | X (Twitter) | Pinterest | Instagram

Looking for Data Analytics Resources?

You’ll find them here:

📚 You Might Also Like...

Here are a few more blog posts you might be interested in:

• 30 Interview Questions to Prepare for Your Next Data Analyst Role

• SQL Best Practices for Writing Clean, Reliable Queries

• Learning New Data Skills While Working Full-Time: How to Make It Work

• Building a Data Analytics Portfolio: What to Include and Where to Start

• You Don’t Have to Be a Math Wizard to Work in Data Analytics

Data With Sarah

Build confidence in data analytics, with clear tips, tools, and lessons that help you grow your career.

By Sarah Rajani

Note: This post includes affiliate links, which help support my work.

✨Your one-stop shop for cleaner queries, smarter dashboards, and fewer late-night Google searches:
The Data Analytics Stash ✨

Ah, the Google Data Analytics certificate…

Every data analyst has an opinion on this one.

Bring up this program in a data meeting, and watch the fun begin.

You either really loved it or really hated it. There’s no in between.

But for a lot of us, it was our gateway into the field, and it helped us solidify our interest in pursuing analytics.

Love it or hate it, many data analysts start with this program, and there’s a reason that over 3 million people (and counting) have registered.

The problem isn’t the program so much as it is people’s expectations.

If you know what you are getting into, then you’ll be much happier.

So if you’re considering taking the program, I shared my experience in my latest post, as well as the cost breakdown and whether you will benefit or whether you should skip it.

And if you’ve taken the program in the past, read the post and let me know your thoughts in the comments.

Did you love it or hate it?

👉 Is the Google Data Analytics Professional Certificate Worth It in 2025?

But Wait, There’s More!

If you’re on Medium, make sure you follow my new data analytics publication, called The Analytics Playbook.

I started the publication because analysts don’t need another AI think piece.

We need SQL tips that actually save time, dashboards that don’t get abandoned, and real discussions on handling stakeholders effectively.

If you’re an analyst or just interested in the field, then give us a follow:

Looking for Data Analytics Resources?

You’ll find them here:

📚 You Might Also Like...

Here are a few more blog posts you might be interested in:

• 30 Interview Questions to Prepare for Your Next Data Analyst Role

• SQL Best Practices for Writing Clean, Reliable Queries

• Learning New Data Skills While Working Full-Time: How to Make It Work

• Building a Data Analytics Portfolio: What to Include and Where to Start

• You Don’t Have to Be a Math Wizard to Work in Data Analytics

Data With Sarah

Build confidence in data analytics, with clear tips, tools, and lessons that help you grow your career.

By Sarah Rajani

Let’s be LinkedIn buddies!

Want more data stuff between newsletters? I’m always on LinkedIn. Connect or follow me! I’m probably on there posting about something right now…

☕ Want to Support My Work?

If something I wrote helped you out, made you laugh, or saved you from rewriting the same SQL query five times… and you feel like sending a coffee my way, here’s where you can do that.

Totally optional. Always appreciated. :)

If you’re looking for more tips like this, I share regularly on my socials. Come and say hi 👋:
LinkedIn | Medium | Facebook | X (Twitter) | Pinterest

Thanks for reading!

—Sarah

It’s not a function.
It’s not temp tables.
It’s not checking joins for the fifth time.

It’s stepping away.

Literally closing my laptop and walking off.

It may sound obvious, but it’s surprising how often we just stay glued to our screens and try to force the solution out.

And that was how I worked, as well.

I used to power through, rewrite sections, comment things out…. Test until I could test no more.

But then one day, I had to take a break. I went to eat, then came back.

And suddenly, the answer was there. Something I couldn’t see before because I’d been staring at the same section of code for too long.

Now when I get stuck on a SQL problem that is driving me insane, I don’t open another Google search.

I walk away.

And trust me, it works.

This blog post breaks down exactly when I do this, what signs I look for, and how this approach has actually saved me hours of pointless rechecking.

Read the full post here →
My Best SQL Debugging Strategy Has Nothing to Do with SQL

Check out my Digital Products:

📚 You Might Also Like...

Here are a few more blog posts you might be interested in:

• 30 Interview Questions to Prepare for Your Next Data Analyst Role

• SQL Best Practices for Writing Clean, Reliable Queries

• Learning New Data Skills While Working Full-Time: How to Make It Work

• Building a Data Analytics Portfolio: What to Include and Where to Start

• You Don’t Have to Be a Math Wizard to Work in Data Analytics

Let’s be LinkedIn buddies!

Want more data stuff between newsletters? I’m always on LinkedIn. Connect or follow me! I’m probably on there posting about something right now…

👀 What do You Want to See Next?

Want me to cover something in an upcoming post? Drop it in the comments. Always looking for good topics — SQL, dashboards, career stuff, anything!

☕ Want to Support My Work?

If something I wrote helped you out, made you laugh, or saved you from rewriting the same SQL query five times… and you feel like sending a coffee my way, here’s where you can do that.

Totally optional. Always appreciated. :)

If you’re looking for more tips like this, I share regularly on my socials. Come and say hi 👋:
LinkedIn | Facebook | X (Twitter) | Pinterest

Thanks for reading!

—Sarah

When I first got into data analytics, I thought learning all the tools would be the hardest part.

It wasn’t.

What held me back more than anything was overthinking.

I entered the data field from a non-traditional background, transitioning from a career in forex. Everything I thought I knew never seemed to be enough. I felt like I was “behind” because I didn’t enter the field directly after college.

I second-guessed decisions that didn’t need that much thought. I wasted time trying to make things perfect when “good enough” would have been fine. And I told myself that if I didn’t know something already, maybe I wasn’t meant for this kind of work.

Looking back, here are some of the things I thought too much about, and what I do differently now. Maybe they can help you, too.

Writing “Perfect” SQL

I remember feeling like every query had to be neat and optimized from the start. Now I start with writing something that runs, then clean it up after if needed. The first version is allowed to be messy; that version is for you, for testing. The final product will be the better version, the one that is properly aliased and organized.

Choosing the “Right” Tool

I would spend too long trying to figure out which tool was best for each task. Now I go with whatever is fastest and gets me to the answer without much issue. Sometimes that’s SQL. Sometimes it’s Excel. Sometimes it’s a combination of tools. I try not to overthink it much anymore.

Once you start getting a lot of requests your way, you’ll understand that time is of the essence. Using the coolest new tool is not practical if there is something faster and easier. Your stakeholders won’t care how you got the answer, just that you got it.

Explaining Too Much

In meetings, I remember walking people through every single insight. I thought that’s what being thorough meant. Now I only explain what matters to the decision at hand.

The rest goes in the appendix, in the documentation, or doesn’t go in at all. If they ask about it, then I am prepared. Otherwise, I move on.

Waiting Too Long to Share

I wanted everything to be perfect before I showed anyone. That included my reports, dashboards, documentation, analyses… I was so worried I would miss something or wasn’t doing it properly, and didn’t want to be criticized.

Now I send drafts earlier on. It saves me time and helps me fix things faster if I can get answers, sooner. People are more helpful when they can give feedback at the right stage.

Trying to Sound Smart

This one took a while to change. I’d talk in a way I thought analysts were “supposed” to talk, with all the technical lingo and big words. But sounding technical doesn’t mean you’re being clear.

Now I try to explain things in the simplest terms possible. That’s what people actually want and need when they are trying to make decisions, especially non-technical stakeholders.

Skip the jargon and talk in a way that makes sense to the person in front of you. You don’t want them walking away confused. If you lose the audience, then you lose the point.

Learning Too Many Tools at Once

I know a lot of us had this nagging thought at some point:

You had to learn everything as fast as possible.

SQL, Python, Tableau, Power BI, Excel….

All the things!

I jumped between learning different tools, but it just confused me more. The goal should really be to take to your time on one topic, practice and learn it well, and only then go onto the next tool. That works better for understanding and retention.

Most of the things I used to overthink came from fear…

Fear of not knowing enough.

Fear of looking unqualified.

Fear of messing up.

But you learn faster when you let yourself get things wrong.

You remember that mistake you made that one time? I bet you didn’t make that mistake again, or at least not quite as badly.

Besides, you work better when you’re not trying to prove anything, to yourself or anyone else.

If you're in that early stage where everything feels uncertain, just know that you don’t need to be perfect.

You don’t need to know everything.

You just need to keep motivated, keep putting in that effort, and asking good questions.

That’s what actually builds confidence. Not the cool dashboard or the perfectly formatted SQL.

Just doing the work, and taking one step at a time. No matter how long it may take.

So if you’re in that headspace now, or maybe imposter syndrome is creeping up on you again, just keep going.

It gets better.

Subscribe now

Recommended Blog Posts

If you haven’t had a chance to check these out yet, here are a few you might find helpful:

• How to Pass the PL-300 on Your First Try

• LinkedIn for Data Analysts: Why Your Profile Matters More Than You Think

• Transitioning into Data Analytics as a Mid-Career Professional: What No One Prepares You For

• You Don’t Have to Be a Math Wizard to Work in Data Analytics

• Learning New Data Skills While Working Full-Time: How to Make It Work

☕ Want to Support My Work?

If something I wrote helped you out or made you laugh, and you feel like sending a coffee my way, here’s where you can do that.

Totally optional. Always appreciated. :)

Buy me a coffee ☕

And come say ‘Hi’👋 on my socials:

I share tips, updates, and behind-the-scenes thoughts here:

LinkedIn | Instagram | Threads | Facebook | X (Twitter) | Pinterest | Medium

Until next time!

—Sarah

Apparently, if you work with data, you must:

• Know how to code like a developer.

• Be a math genius.

• Predict the future.

• Build machine learning models in your sleep.

None of that is true. But these assumptions keep showing up, on job descriptions, in interviews, and even in casual conversations.

So let’s clear the air.

I’ve put together the 10 most common myths I’ve seen floating around about data analytics and unpacked what’s actually true.

Because if you’re trying to break into this field, these misconceptions can seriously mess with your confidence, or send you chasing the wrong skills altogether.

Read the full list and what to focus on instead →

Are you a Medium member?

If you prefer reading your content on there, check out the post here.

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Here are a few more blog posts you might be interested in:

• 30 Interview Questions to Prepare for Your Next Data Analyst Role

• SQL Best Practices for Writing Clean, Reliable Queries

• Learning New Data Skills While Working Full-Time: How to Make It Work

• Building a Data Analytics Portfolio: What to Include and Where to Start

• You Don’t Have to Be a Math Wizard to Work in Data Analytics

Let’s be LinkedIn buddies!

Want more data stuff between newsletters? I’m always on LinkedIn. Connect or follow me! I’m probably on there posting about something right now…

👀 What do You Want to See Next?

Want me to cover something in an upcoming post? Drop it in the comments. Always looking for good topics — SQL, dashboards, career stuff, anything!

☕ Want to Support My Work?

If something I wrote helped you out, made you laugh, or saved you from rewriting the same SQL query five times… and you feel like sending a coffee my way, here’s where you can do that.

Totally optional. Always appreciated. :)

Buy me a coffee ☕

If you’re looking for more tips like this, I share regularly on my socials. Come and say hi 👋:
LinkedIn | Instagram | Threads | Facebook | X (Twitter) | Pinterest

Thanks for reading!

—Sarah

But LinkedIn?
It doesn’t feel as important.
It might even feel awkward, putting yourself out there for all to see…

I know, I felt the same way when I first transitioned into data.

But here’s the thing: LinkedIn can open way more doors than you think, especially when you’re newer to data or switching careers.

Building relationships with people in your industry is one of the best advantages to creating a profile! You’d be surprised how many people are on the platform, sharing their experiences, their advice, and neat things they learn.

In this post, I break down:

✅ Why your profile matters.
✅ How hiring managers and recruiters actually use LinkedIn.
✅ Common mistakes data analysts make on their profiles.
✅ What’s worth focusing on (and what isn’t).

If you want to set up your LinkedIn profile, or even just update it, this post is for you.

👉 Read the full post here

📚 You Might Also Like...

Here are a few more blog posts you might be interested in:

• 30 Interview Questions to Prepare for Your Next Data Analyst Role

• SQL Best Practices for Writing Clean, Reliable Queries

• Learning New Data Skills While Working Full-Time: How to Make It Work

• Building a Data Analytics Portfolio: What to Include and Where to Start

• You Don’t Have to Be a Math Wizard to Work in Data Analytics

Want more data stuff between newsletters? I’m always on LinkedIn. Connect or follow me! I’m probably on there posting about something right now…

👀 What do You Want to See Next?

Want me to cover something in an upcoming post? Drop it in the comments. Always looking for good topics — SQL, dashboards, career stuff, anything!

☕ Want to Support My Work?

If something I wrote helped you out, made you laugh, or saved you from rewriting the same SQL query five times… and you feel like sending a coffee my way, here’s where you can do that.

Totally optional. Always appreciated. :)

Buy me a coffee ☕

If you’re looking for more tips like this, I share regularly on my socials. Come and say hi 👋:
LinkedIn | Instagram | Facebook | X (Twitter) | Pinterest

Thanks for reading!

—Sarah

This post is your go-to guide.

Here’s what you’ll find inside:

✅ 30 essential interview questions, spanning SQL, tools, scenarios, and behavior.
✅ Advice on what hiring managers are really asking.
✅ Tips on crafting answers that sound like you, not a script.

Feeling more confident walking into interviews starts with good prep. If you're serious about landing that role, start here.

BONUS:

I created a FREE Notion template to help you with your interview preparation. Check out the link in the blog post.

👉 Read the full post here

📚 You Might Also Like...

Here are a few more blog posts you might be interested in:

• SQL Best Practices for Writing Clean, Reliable Queries

• Learning New Data Skills While Working Full-Time: How to Make It Work

• Building a Data Analytics Portfolio: What to Include and Where to Start

• You Don’t Have to Be a Math Wizard to Work in Data Analytics

Want more data stuff between newsletters? I’m always on LinkedIn. Connect or follow me! I’m probably on there posting about something right now…

👀 What do You Want to See Next?

Want me to cover something in an upcoming post? Drop it in the comments. Always looking for good topics — SQL, dashboards, career stuff, anything!

☕ Want to Support My Work?

If something I wrote helped you out, made you laugh, or saved you from rewriting the same SQL query five times… and you feel like sending a coffee my way, here’s where you can do that.

Totally optional. Always appreciated. :)

Buy me a coffee ☕

If you’re looking for more tips like this, I share regularly on my socials. Come and say hi 👋:
LinkedIn | Instagram | Facebook | X (Twitter) | Pinterest

Thanks for reading!

—Sarah

But what if you’re mid-career, already working in another field, and now trying to move into data?

The reality is, it’s a different experience (an experience I know all too well).
You bring a lot with you, but you also face challenges no one talks about.

In this post, I share:

✅ What’s different about transitioning mid-career.
✅ Why it sometimes feels harder than it “should.”
✅ What actually helps (and what gets in the way).
✅ How I managed this transition, and what I would do again.

If you’re switching into data analytics, or thinking about it, this will help you feel a little more prepared for what’s ahead.

👉 Read the full post here

📚 You Might Also Like...

Here are a few more blog posts you might be interested in:

• SQL Best Practices for Writing Clean, Reliable Queries

• 30 Interview Questions to Prepare for Your Next Data Analyst Role

• Data Analysis Project Guide: How to Structure and Present Your Work

• You Don’t Have to Be a Math Wizard to Work in Data Analytics

Want more data stuff between newsletters? I’m always on LinkedIn. Connect or follow me! I’m probably on there posting about something right now…

👀 What do You Want to See Next?

Want me to cover something in an upcoming post? Drop it in the comments. Always looking for good topics — SQL, dashboards, career stuff, anything!

☕ Want to Support My Work?

If something I wrote helped you out, made you laugh, or saved you from rewriting the same SQL query five times… and you feel like sending a coffee my way, here’s where you can do that.

Totally optional. Always appreciated. :)

Buy me a coffee ☕

If you’re looking for more tips like this, I share regularly on my socials. Come and say hi 👋:
LinkedIn | Instagram | Facebook | X (Twitter) | Pinterest

Thanks for reading!

—Sarah

“I'm not good at math, so I probably can’t do data analytics.”

If you've ever thought this (or heard someone else say it), this post is for you.

One of the most common things that holds people back from starting a data career is the belief that you need to be a “math person.”

I used to think this too, but it’s just not true.

In this post, I share:

✅ Why you don’t need to be a math expert to work in data.
✅ What skills actually matter day-to-day in analytics.
✅ The kinds of math you do need (and what you probably don’t).
✅ Why this myth still shows up, and how to get past it.

If you’re considering a career in data, or trying to grow your skills, this will give you a better sense of what really matters.

👉 Read the full post here

📚 You Might Also Like...

Here are a few more blog posts you might be interested in:

• SQL Best Practices for Writing Clean, Reliable Queries

• 30 Interview Questions to Prepare for Your Next Data Analyst Role

• Data Analysis Project Guide: How to Structure and Present Your Work

• Transitioning into Data Analytics as a Mid-Career Professional: What No One Prepares You For

Want more data stuff between newsletters? I’m always on LinkedIn. Connect or follow me! I’m probably on there posting about something right now…

👀 What do You Want to See Next?

Want me to cover something in an upcoming post? Drop it in the comments. Always looking for good topics — SQL, dashboards, career stuff, anything!

☕ Want to Support My Work?

If something I wrote helped you out, made you laugh, or saved you from rewriting the same SQL query five times… and you feel like sending a coffee my way, here’s where you can do that.

Totally optional. Always appreciated. :)

Buy me a coffee ☕

If you’re looking for more tips like this, I share regularly on my socials. Come and say hi 👋:
LinkedIn | Instagram | Facebook | X (Twitter) | Pinterest

Thanks for reading!

—Sarah

It’s easy to say “keep learning” when you’re in a data career.

But it’s easier said than done, especially when you’re already working 40 hours a week (or more), it can feel impossible to squeeze in time for learning SQL, Power BI, Python, or whatever new tool you keep hearing about.

You sit down after work, and your brain is toast.

Weekends? Maybe. But you also have a life to live.

If this sounds familiar, then keep reading.

I wrote about how I managed to build new skills while working full time, and what actually worked for me (spoiler: it wasn’t just “better time management”).

Inside the post:

✅ Why most advice about learning while working is unrealistic.
✅ How to build consistency when your schedule is unpredictable.
✅ What worked for me as I added new tools to my skill set.
✅ And how to make learning fit your life, not the other way around.

If you’re trying to grow your data skills and wondering how to make it work, you’ll want to read this one.

👉 Click here to read the full post

📚 You Might Also Like...

Here are a few more blog posts you might be interested in:

• SQL Best Practices for Writing Clean, Reliable Queries

• 30 Interview Questions to Prepare for Your Next Data Analyst Role

• Data Analysis Project Guide: How to Structure and Present Your Work

• Transitioning into Data Analytics as a Mid-Career Professional: What No One Prepares You For

Want more data stuff between newsletters? I’m always on LinkedIn. Connect or follow me! I’m probably on there posting about something right now…

👀 What do You Want to See Next?

Want me to cover something in an upcoming post? Drop it in the comments. Always looking for good topics — SQL, dashboards, career stuff, anything!

☕ Want to Support My Work?

If something I wrote helped you out, made you laugh, or saved you from rewriting the same SQL query five times… and you feel like sending a coffee my way, here’s where you can do that.

Totally optional. Always appreciated. :)

Buy me a coffee ☕

If you’re looking for more tips like this, I share regularly on my socials. Come and say hi 👋:
LinkedIn | Instagram | Facebook | X (Twitter) | Pinterest

Thanks for reading!

—Sarah