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

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.

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

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

Universal Banker / Bank Teller

Academy Bank

Personal Banker

Fry's Food and Drug

Organize and stock produce department, as well as greet and assist customers to make their grocery shopping experience quite enjoyable.

Produce Clerk

Holy Spirit Catholic Newman Center

- Assisting staff members in an office environment
- Organizing and running events for college students in a religious setting
- Scheduling volunteers for daily and weekly masses

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The Battle

Matt Mike

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Posts

Engagements

Likes

Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Matt Mike's LinkedIn Performance

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