Data Analyst | Tableau Consultant | Author of How to Become a Data Analyst

If you're reading this you probably either:
1. Want a job in data. 
2. Want a friend in data.
3. Need a data analyst. 

If you're #1, I was you, just one year ago! I've shared how I went from beginner to experienced data professional since the beginning.

Its my goal to create the kind of content a younger version of me would have wanted to consume!

#2, thanks for being here! Feel free to give me a wave. Lets be social!

#3's, hello 👋. If you haven't yet, check out my portfolio site, or my Annie's Analytics company page on here where I offer consulting services.

Heres my story. 

In February of 2022, I decided to learn data analytics for fun. I created a Tik Tok account, and started documenting my journey to learn this new hobby (@anniesanalytics). 

Very soon, I realized that every day I was waking up and just wanting to write SQL, build visualizations, learn Python.... Work with data! So, I decided that once I finished graduate school (in Healthcare) in July, I was going to become a data analyst. 

Along the way, I have shared here and on Tik Tok everything I can about what it's like to learn data analytics, and how you can do it for free or at least very cheaply. I've shared about the ups and downs of job searching. I've even shared about how I have built a portfolio, and set myself up as a real analyst. 

Now I also do YouTube videos, especially my series where I invite other data analysts to have a coffee chat with me, but we live stream it! We talk about our journeys into data and what our jobs look like now. https://youtube.com/playlist?list=PL3wIL0Blsv2vf8aAjTQXo017YntAXqrZc


Want to see my Portfolio as it was when I got my first job in analytics? I left it here in exactly the same state that it was when I got my job in July of 2022 to serve as an example to you, if you are a job seeker now! https://anniesanalytics.wixsite.com/annie-nelson/projects-6 

Want to see my current portfolio I am using now that I have gained some more skills? https://anniesanalytics.carrd.co/

Or the LinkedIn group here: https://www.linkedin.com/groups/12635532

Discord here! https://discord.com/invite/m9vZKtReFM

Annie Nelson

Hitting the title of "senior data analyst" was a revelation for me, because I realized that the path ahead suddenly had a lot more forks and turns than it did on the way here.

Progressing Junior -> Senior felt like a very linear path. I took detours by becoming a SME in Tableau as a junior, but the corporate path was still well paved.

I try to be proactive about my career - I am very happy where I am right now and I'm not in a rush to keep progressing, but I understand that career steps are not done in the moment. I should always have a direction.

But what IS my direction now?

The next level on my team is "staff", which could be a target. But what does it even mean to be a staff level data analyst?

Since I got promoted 2x this year, I know it would be quite a while before I could be promoted again to staff. I suppose that would give me a long time to figure out what staff even means on my team.

Up isn't the only way to go.

I enjoy working with the business - more than I enjoy data for the sake of data. One option could be moving from the data team to a business team.

Or, like many do analysts, I could go the way of taking on a true business role and drop the 'data analyst' from my title - such as product manager.

Since I haven't held any of those roles before, I would have to do a lot of research to figure out what steps I'd need to take if I wanted to make a change like that.

Another option is to move to an organization that is bigger / smaller. If I worked at a startup I would get the chance to wear a lot more hats, and likely be much closer to the business strategy than I do now as an analyst on a data team at a public company.

I suppose the road has always been this wide, but I didn't realize it because I had been focused on what was right in front of me - improving myself and my skills to go in the direction of senior.

For me, it wasn't really about the senior title. What appealed to me was that "Senior" gave me a benchmark of qualities and skills that I (a former nanny) could aspire towards as I learned to be an effective tech person.

I guess you could say that I'm looking for my next benchmark - who do I want to be? What skills do I need to cultivate? What kinds of projects should I be getting experience with?

Eventually I will figure it out 🫡

If you want to know how the AI bubble is going, here's the top comment from a news post about big AI changes to coming to Gmail.

AI will be implemented throughout - it can read, respond to, and prioritize your emails for you. And it's turned on automatically! 

Notice the likes.

I'm considering counter-pitching the AI company that reached out to me to help me "10x my posting efficiency by recycling my existing popular content" 

and offering to pay them $10 to send me their client list so I can make sure to unfollow them.

One of the reasons LinkedIn has become so tedious recently is that it's nearly impossible to find an original thought on here.

The space once occupied by thought leaders is now crowded by people who know how to gather an emotional reaction out of the largest amount of people.

Yes, it's conventional content creator wisdom to reuse your old posts that have performed well. I don't care. Its boring. 

Followers is just a vanity metric if most of your followers are just going to skip all of your posts because they've seen the content before (multiple times).

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/

Matt Mike

Not 1, not 2, but 3 hernia’s repaired.

Had surgery the other day. 

Recovery has been brutal but I’m so glad to finally get this done. These hernias have been a major impairment to physical activity and a daily discomfort.

Super grateful to my wife who’s been taking care of me, the kids, and everything else while I hobble around like an old man.

Day 3 of a 6-8 week recovery✌🏻

Business Intelligence Developer 🤘 | BI & Analytics Consultant | YouTube @ Matt Mike | Helping non-tech professionals break into data and make $30k+ more with the Data Career Makers community

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I've applied to 1,000s of jobs in my career.

Most led nowhere.

But the problem wasn't my resume or skills.

The problem was treating job hunting like a numbers game.

(the spray and pray method).

Applying to 50 jobs a week → exhausting.
Applying to 5 targeted opportunities → strategic.

Strategic job hunting = better interviews, faster offers.

Here's how I'd approach the job hunt in 2026 if I had to start over:

1. Build relationships before you need them

Most people wait until they're desperate to start networking. 

They send cold messages, ask strangers for referrals, and wonder why nobody responds.

This is backwards.

Instead I'd spend 30 minutes a day engaging with people in my target companies.

Comment on their posts, share their content, add genuine value.

When you build relationships first, opportunities come to you.

You don't need to beg for referrals when people already know your name.

2. Post content that showcases your work

Resumes can get lost or ignored.

LinkedIn posts are living proof of what you can do.

I'd post 3x a week about projects I'm working on, problems I've solved, tools I'm learning.

Not generic advice. Actual work.

This does two things: 1) it proves you know your stuff and 2) it makes you visible to hiring managers who are scrolling LinkedIn looking for talent.

3. Apply like you mean it

I'd rather spend 20 minutes on one application than 10 minutes on twenty.

For each role I'd research the company, customize my resume to match their exact needs, and write a cover letter that shows the value I bring.

Then I'd find the hiring manager on LinkedIn and send a short message explaining why I'm interested.

Most people won't do this because it takes effort.

But that's why it works.

tl;dr:

1. Network before you need it. 
2. Prove your skills publicly.
3. Apply with intention.

ps - got a vid on this topic publishing soon. check out my channel so you don't miss it: https://lnkd.in/dpMCPTmH

I love the problem solving side of data analytics and BI work.

Being handed an ambiguous problem that you have to turn into a clear, concrete solution.

Sometimes that means defining the right metric. Sometimes it’s building a custom visual, designing the right report layout, automating a process, or just getting data from point A to point B.

The moment when a solution finally clicks fills me with a sense of pride and excitement. It's one of my favorite things about this type of work!

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

There are 2 options for shifting into technical careers outside of formal degrees.

1) Teach yourself
2) Bootcamps and/or coaching

Here are the pros and cons of each, as I see them.

1) Teach yourself

Pros:
- Cheaper
- Flexible
- Bragging rights when you finally make it

Cons:
- Takes longer
- Potentially more stressful
- Can waste time going in the wrong direction

My thoughts: This can work for people who aren't under too much pressure and have the time and flexibility to make the career jump when ready.

2) Bootcamps and/or coaching

Pros:
- Move more quickly
- Accountability and structure
- Guidance on exactly what to do and when

Cons:
- More expensive
- Stricter time commitments
- Lots of unqualified programs and coaches out there

My thoughts: Ideal for people who have the budget, want fast results, and the accountability and structure to make it happen.

My honest opinion is that in this market, if you're starting from zero, option 1 is becoming harder to pull off. Doesn't mean you can't do it, but you have to understand that it will take lots of time and effort.

Because of this, I think option 2 is actually becoming MORE valuable, not less. Implementation and guidance goes a long way when utilized correctly.

As far as programs I'd recommend, the 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗔𝗰𝗰𝗲𝗹𝗲𝗿𝗮𝘁𝗼𝗿 program by Avery Smith​ is my top choice.

It has all the top things I look for in programs like this:

- Learn the full analytics tech stack
- Guidance on navigating the actual market
- Internship opportunities
- Coaching and peer support

And Avery himself is an incredibly qualified Data Scientist.

Check out his program here: https://lnkd.in/gR9kq_r5

Either of the 2 options I described above can work, but which is best depends on your situation.

___
PS - If you work in data now, did you go with option 1, 2 or did you get a formal degree?

#dcjpartner

Had a great time at our low-key Phoenix, AZ happy hour last night!

Awesome turnout. Got to meet some great people!

It was also my first time meeting in person a few people that I've known from LinkedIn for quite some time now.

Andrew Madson 
Madison Schott 
Monica Kay Royal (won't let me tag you for some reason???)

We're thinking of doing these quarterly. 

If you're in Phoenix and missed this one, hope you can make it to the next one!

___
PS - still recovering from my hernia surgery but I couldn't miss this. Really pushed myself to be there. Couldn't stay long due to the pain, but glad I made it :)

I don't like 5-year plans.

You can't even predict where you'll be 1 year from now, let alone 5 years.

When I look back on the last 5 years, very little of what I thought it would look like actually came to fruition.

But plenty of good things still happened!

Just not what I expected to happen. Not even close.

So rather than chasing a 5-year plan, try just focusing on the next few months. That's where you have the greatest amount of leverage and control.

Don't burden yourself by thinking too far into the future. It won't do you much good.

A lot happened for me in 2025.

I've talked about bits and pieces of it here on LinkedIn, but I just posted a full video about it for anyone interested.

I like doing these yearly check-in type videos.

It's just nice to process everything out loud.

https://lnkd.in/g8i8PDAe

PS - thanks to everyone for the well wishes on my recovery from surgery. Today is day 5 and I'm getting a little bit stronger each day :)

Open video: Data Analyst Year In the Life: 2 Moves, Lost My Dream Tech Job, and What I'm Changing in 2026 on youtu.be

Data Analyst Year In the Life: 2 Moves, Lost My Dream Tech Job, and What I'm Changing in 2026

There's a lot of talk about data and AI.

And I hear most from people outside of the data space about what will happen to technical jobs.

So, in this video I share my boots-on-the-ground take on the situation. What I'm seeing, researching, and hearing from my many peers around and above me in the data and AI space.

https://lnkd.in/gdmDtEJb

___
PS - getting back to a regular schedule with uploads. My goal for 2026 is actually to increase volume to 2 uploads per week. We'll see if I can manage that lol

Open video: Will AI Replace Data Analysts in the Next 10 Years? on youtu.be

Will AI Replace Data Analysts in the Next 10 Years?

You don't have to sound like an idiot anymore.



Check out Count here:
https://lnkd.in/gKFDZJgN

#countpartner

Some people call pie charts bad.

It's like the "Is a hotdog a sandwich?" debate of data viz.

But I think it completely depends on the context.

There's nothing wrong with pie charts inherently.

Comparing 2 values against each other is a great use case.

The problem shows up when you have too many values.

Too difficult to interpret quickly. 
Data labels get smushed together.

Can you see the data clearly?

The second they start getting smushed, swap the visual.

(rule of thumb is 4-5 values, but it depends)

Especially when your dashboard is already full of bar and column charts.

So if you're avoiding pie charts because someone told you they're bad:

1. Ask yourself how many values you're showing
2. Consider if variety would help your dashboard
3. Check if the data labels are readable
4. Then decide

Context matters.

Which camp are you in on this?

___
PS - I just started a community for people breaking into data careers. Check it out here (launch pricing still active): https://lnkd.in/gjY7-wyJ

The data job market looks different this year.

More data jobs than ever before, but also more saturated.

As someone who was laid off and on the job hunt again mid-2025, I have some thoughts on how I'd do it all again 2026. Especially if I was starting from scratch.

In this video, I cover those thoughts.

https://lnkd.in/gvPJxsbq

Open video: The EASIEST Way To Become a Data Analyst in 2026 (skills + portfolio + job search) on youtu.be

The EASIEST Way To Become a Data Analyst in 2026 (skills + portfolio + job search)

I'm a fan of using AI for things that protect my time while allowing me to remain in the driver seat.

One example of this is deck building.

I create the content.
AI creates the packaging.

That way, the words are still mine, but AI can take care of the organization and creative elements of my presentation.

Recently, I've been using Gamma​ for this.

With it I can just:

1. Write my executive summary and findings
2. Plug it into the app
3. Enter a few style choice settings
4. Generate my deck in minutes
5. Edit as needed

I still have complete control.

I'm simply outsourcing the packaging.

They recently integrated NanoBanana from Google Gemini. A nice little upgrade.

https://lnkd.in/gD8hMxkJ

Try it out for your next slide deck.

ps - have you integrated ai into your deck building? what have you found helpful?

Curious...

...also, feel free to leave suggestions in the comments if you have a different answer than in the poll :)

___
ps - i got one of these. we're steadily growing! you can check it out here: https://lnkd.in/gjY7-wyJ

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The Battle

Annie Nelson

Matt Mike

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