Yo, I'm Matt Mike 👋

(yes, Mike is my actual last name).

My career path has been far from linear. Here are the cliff notes (that's still a thing, right?)

2015: graduated with an English degree
2016: became a teacher
2017: became a dean of students
2019: left education for B2B sales
2019: hated sales. took a pay cut to become an operations analyst
2021: got promoted to operations supervisor

2022 and onward: became a business analyst (FIRST DATA JOB). Started documenting the journey on social media where I now have a combined following of 100,000+ tech professionals. I've been through a few different data roles with progressive complexity and now do BI consulting while continuing to help others progress their tech careers through content.

Because of my background, I have a passion for helping people with non-technical backgrounds break into tech and advance their careers. My technical passion is business intelligence analytics.

🤝🏻 Brands: mjomike@gmail.com
🎥 YouTube: @mattmike
📩 Newsletter: https://thdatapoint.substack.com/

I changed careers at 31.

I was a teacher, then a Dean of Students first.

From there, I spent a few years in a non-technical corporate role. But that was my introduction to technical tools.

I decided I wanted to get into data analytics and went for it. The process start to finish took about 6 months.

People often think that you should be settled into a career in your 30s, but it's never too late to pivot from one area to another.

We put a lot of pressure on ourselves to "figure it out" but life isn't always so linear.

If you want a change. Make it happen.

Matt Mike

BI Developer & Analytics Consultant 🤘 | YouTube @ Matt Mike | Former Educator & Dean of Students

You can learn Data Analytics for $0 this week and you have no excuse not to.

DataCamp is making ALL 600+ courses completely FREE from February 16-22

This includes career tracks, courses, and even certifications.

Want to break into data? Try one of these tracks:

↳ Data Analyst in SQL Track → https://lnkd.in/gpnFZCFm
↳ Data Analyst in Power BI Track → https://lnkd.in/gR6xkh4W
↳ Python Fundamentals Track → https://lnkd.in/g3xnmDFE

I learned SQL largely through DataCamp. Their lesson plans, interactive learning, and guided projects make it easy to build actual skills.

Or browse all courses here → https://lnkd.in/g3xnmDFE

This is the best way to spend your week if you're serious about getting into data.

♻️ Share if you're planning on taking advantage!

#datacamppartner

🗞️ My Newsletter → https://thdatapoint.substack.com/
📹 YouTube Channel → https://www.youtube.com/@MattMike
👨‍💻 1:1 Coaching → https://calendly.com/matt_mike/60-min-data-career-roadmap
📚 Career Resources → https://mattslinks.carrd.co/
🤝 Brand Partnerships → mjomike@gmail.com

Key Info:
▶️ Product Manager in EdTech
▶️ Power BI development aficionado
▶️ Data analysis using Excel, SQL, & Python
▶️ Former teacher and Dean of Students
▶️ Husband and father of 2 kiddos

I bootstrapped my way into the Data field from a non-technical background and have a passion for helping others do the same (without going back to school for a $50K degree).

DataCamp

Business Intelligence Developer 🤘

You find a job posting.

It has 1,297 application submissions.

You apply anyway.

You submit your resume to the portal.

Despite all your information being on the resume, it requires you to re-submit everything again. Manually. Line by line. Company zip codes and all.

You provide your gender and nationality for the thousandth time.

You click submit.

The portal crashes.

Nothing was submitted.

This is the job market in 2026.

BI Developer & Analytics Consultant 🤘 | YouTube @ Matt Mike | Helping professionals break into data careers @ Data Career Makers

I used to think being a Data Analyst was just running SQL queries and making charts all day.

Turns out, that's exactly what it is. But here's what nobody tells you about the job:

1. Meeting Overload - Half your time explaining why the data says what it says.
2. Data Quality Issues - A lot of time cleaning messy data.
3. Stakeholder Management - Everyone thinks their request takes "just 5 minutes."
4. Constant Revisions - Reports are often an iterative process
5. Documentation Gaps - Nobody knows where the data actually comes from.

The technical skills are the easy part (relatively speaking). Writing queries, building dashboards, creating visualizations. You can learn most of what you need in a few months.

The best analysts aren't the ones who do the most complex work. Rather, they're the ones who can explain confusing data in a way that drives action.

How to win LinkedIn as a tech influencer:

1. Get a job in MAANG
2. Get laid off 6 months later 
3. Put ex-MAANG company in your headline
4. Enjoy your new prestige. It will never expire.

SQL is a fundamental analytics skill.

It's the language of databases and how we query those databases for the information we need.

My latest read, "𝑆𝑄𝐿 𝑓𝑜𝑟 𝐷𝑎𝑡𝑎 𝐴𝑛𝑎𝑙𝑦𝑡𝑖𝑐𝑠" shows you how to do just that.

But it goes far beyond the basics.

Into things like:

↳ Manipulating data with Python
↳ Presenting, transforming, and updating data
↳ Defining datasets from existing datasets
↳ Window functions
↳ Performant SQL
↳ Processing JSONS and Arrays
↳ Advanced data types
↳ Inferential statistics

And best of all, it's practical.

Big thanks to the authors:

Jun Shan​
Haibin Li
​Matt Goldwasser​
Upom Malik​
Benjamin Johnston

Looking forward to learning some cool stuff :)

Grab the book here if you're interested: https://packt.link/0oLy1

#packtpartner

SQL is still a top skill for data analytics in 2026.

Even with AI advancing, you need SQL to land analyst roles and think critically about data.

Here's the thing: most people learn it wrong. They memorize syntax instead of writing queries.

In this video, I provide guidance on learning SQL:

- Why it still matters to learn it
- The wrong vs the right way to learn it
- Which environment to pick + 1st dataset
- The question progression method
- A 30-day roadmap for learning
- What to do beyond 30 days

Consistent, hands-on practice beats passive learning every single time.

Check it out here: https://lnkd.in/gGDzqSBC

___
ps - did you have to complete a SQL interview for your current data role? Tell us about it below.

I've been using the latest Power BI Modeling MCP with Claude lately in some of my work and it's insane.

You can achieve huge amounts of heavy lifting through prompts alone.

1. Set up the integration
2. Connect Claude to your report
3. Prompt Claude
4 See your report change in real time. 

Crazy.

It's scary and exciting all at the same time.

I feel immense power in my report building as a result.

Claude still can't touch the visual layer of your report - which I think for now is a good thing - and it also can't alter your M code in Power Query, but here's what it can do:

↳ Create calculated columns and measures
↳ Create measure tables
↳ Organize measures
↳ Create table folders & column hierarchies
↳ Add column/measure descriptions
↳ Create documentation for your report

Again, Claude is making these changes to your report for you when you prompt. Wild.

Have you tried this yet? Thoughts?

ps - I'm thinking of doing a video showing how to set up the integration and demo'ing what you can do. Should I?

Not enough job seekers are building in public.

But the ones who do often land jobs faster.

I've noticed something interesting over the years. The people who share their learning journey publicly often get faster results.

It's not that recruiters flood their DMs. Though you might have some reach out.

It's because of what building in public does for you:

1. Drive - you actually complete projects instead of leaving them half-done
2. Profile boost - recruiters see someone actively growing their skills
3. Feedback - other people give you perspectives that help you learn faster
4. Accountability - you follow through on what you post about
5. Knowledge - talking about what you're learning helps you understand it better.

I see people hesitate because they think their work isn't good enough to share. Or they're worried about what others might think.

But it doesn't matter. Just treat your content like a blog.

If you're job searching and not posting about what you're learning, you're missing out. The direct and indirect benefits are worth it in my opinion.

PS - have you done this or do you know someone who has?

Instantly become a better data analyst by:




1. Asking better questions before you build anything

2. Learning one thing deeply instead of everything poorly

3. Spending more time understanding the problems of the business

If I'm being honest, I feel constantly behind with AI.

No matter how much I use it.

I use AI for literally everything. I've 10x'd workflows for so many things...

...and yet, every time I open LinkedIn, someone is sharing about how they 1,000x'd something using methods and tools I've never touched.

Every time I open LinkedIn. I can't escape it.

It's exhausting.

I start feeling discouraged.
I start panicking a bit.
I start feeling behind.

As soon as I learn of one method, a new one pops up that makes me feel behind the curve again.

The methods I don't know or am not using start stacking and I get overwhelmed.

And tbh, I know some of it's grifting. Some of it's legit and genuine. Other times, it's people posting about some method they don't even use because they know it'll get views. The irony is that they probably used AI to instruct them on the entire workflow and what to say.

But it STILL makes me anxious when I see it.

It's a constant race.

This can't just be me.

I think everyone is feeling this way.
Everyone is figuring it out as they go.
They have to be. It's all so new.

So if you feel behind...well, everyone else is right there with you, no matter how much AI they use.

At least that's the vibe I get.

The solution? I have no idea.

We're all racing towards endless optimization to try and stay ahead and everyone is panicking to some degree.

𝗣𝗿𝗼: Time, effort saved, capabilities increased.
𝗖𝗼𝗻: Constant anxiety about adoption.

___
ps - please tell me I'm not alone on this.

Teachers make great analysts.

Here's what I learned as a former Dean of Students that translates perfectly to data:

1. Pattern Recognition

Teachers spot trends in student behavior, learning gaps, and classroom dynamics daily. That's literally what analysts do with data, identify patterns and anomalies.

2. Simplifying Complex Ideas

You have to explain difficult concepts to people who don't understand them yet. In data, you're constantly translating technical findings for non-technical stakeholders.

3. Asking the Right Questions

Good teachers don't just give answers, they ask questions that lead to understanding. That's exactly what drives good analysis, knowing what questions to ask of your data.

4. Adaptability

Lesson plans change, students have different needs, and you adjust on the fly. Data projects are the same. Requirements shift and you pivot.

This isn't just me either. I've seen dozens of former educators crush it in data roles because they already have the core skills.

If you're a teacher thinking about transitioning into data, you're more qualified than you think.

The skills transfer better than most people realize.

Here's your sign to do something nice today.

I even built a simple app with Replit​ to help you.

1. Press the button
2. Get an actionable prompt
3. Do the thing

Do that here: https://lnkd.in/g7HRCtpm

They're all easy-to-do things that will make a difference in someone's day.

Sometimes we just need a little nudge, to inspire us to do something nice.

Making someone feel good makes you feel good.

Total win-win.

Build your own thing with Replit here: https://lnkd.in/g4_TeMRs

#replitpartner

Contract roles are very common in data.

But are they worth it?

I’ve done them. I have my thoughts. Curious how others feel about them.

This has been an incredible project to be a part of. I love my consulting work!

Working with local government is especially rewarding because you get to see the impact your work makes in real time. Your serving the public in a more "behind the scenes" kind of way.

AI Strategy & Talent Acquisition for Smart Cities & SMBs | Moving Organizations from AI Concepts to Real-World Implementation & Impact | CEO, Smart Talent AI

Great to be back in SF to meet with my favorite clients and candidates!

Landed and went straight into a City Council meeting.

Had the honor of presenting Smart Talent AI’s Smart City dashboard work to the Mayor and Council — showing how data can drive transparency, accountability, and faster action for residents.

This was all as a result of the hard work by my team - Cuong Nguyen Ramesh Casuba Sam Weisman Matt Mike  

Grateful for our city partners who move fast and trust innovation.

This is why we build.
Not for decks.
Not for hype.
But for real cities. Real people. Real outcomes.

DM me for more details on the Dashboard and how we can help your city!

Onward.

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