Alex Freberg

This week we are starting our PostgreSQL Series! This series we will be going beyond just queries, but we will be starting with it to build the base. We will also be learning about connecting databases to apps, using APIs, and more. PostgreSQL has become one of the most popular SQL Databases to work with due to the rise of AI. PostgreSQL became the default for AI apps because pgvector lets you store embeddings right next to your structured data with no separate vector database needed. youtu.be/USOqNVz3gXQ

Kayaking with the family this Memorial Day! Feels good to get out on the water. Spending time with the ones you love is always a good ROI.

DAX is what separates Power BI users from Power BI developers. Most people can drag fields onto a canvas and call it a dashboard. But the moment someone asks for year-over-year growth, a running total, or a metric that respects filters the way the business actually thinks - you need DAX. And the first real test is knowing when to use a calculated column vs a measure. Get that wrong and your model bloats, your reports slow down, and your numbers stop making sense when someone clicks a slicer. Get it right and you stop being the person who builds reports and you become the person who builds models other people build reports on.

Listen, I know people are trying to grow their brands and get noticed - but  optimizing for engagement is super lame. Why don't you just be you - write interesting content and build things and share things you actually like. Stop trying to fit your content for the masses when maybe you need to be bring people into your fandom - who you are. The people worth having around will find you because of who you are, not because you cracked the algorithm.

In 24 hours 28k people started the 2026 Data Analyst Bootcamp! 3 million people started the first one I launched 3 years ago, but only around 10k people finished. That’s a 99.7% dropout rate. So if you complete it and put in the work you’re proving you have a lot of determination and perseverance that most people don’t. Use this time to upskill, learn, and advance your career!

The new 2026 FREE Data Analyst Bootcamp is live! Here's what you'll learn: - Data Fundamentals - MySQL - @Microsoft Excel - @tableau - Microsoft Power BI - Python - Pandas - Building a Portfolio Website - Creating a Resume - Practicing for Technical Interviews - @awscloud - @Azure - Git and GitHub - R Programming - @databricks - How to use LinkedIn to Land a Job That's a lot! All packed into one long 28 hour and 41 minute video. Over the next year or so, I'll be creating new lessons on the following - @alteryx - @Snowflake - PostgreSQL - @duckdb - Statistics - and more! Sometime in 2027 I'll release an updated Bootcamp with these included! This Bootcamp was made with a lot of love and I hope you all learn a ton from it. The data community has given me so much so I'm glad to give back and pass it onto the next generation. Happy learning! youtube.com/watch?v=cnjhHZ…

I currently run 3 businesses: 1. Alex The Analyst on YouTube I say "business", but this one is my lowest revenue and time investments, but I do make some money from it. I do it because I love it and have always loved it - this takes maybe 5-10 hours per week. 2. Analyst Builder This is my ed-tech platform to teach people Analytics and help them land jobs faster. This takes more time and I have a whole team that supports this platform. This takes 20-30 hours per week. 3. Alex Analytics LLC This is my consulting business where I work with tech companies and startups. I do everything from helping with pricing strategy, data migrations, data analysis, to creating content. This takes 30-40 hours per week. I didn't start out with all 3, they evolved over time. I started with my YouTube channel, and as that grew, I slowly started consulting. I started a small mentorship program and as that grew I created Analyst Builder to serve more people. Things don't happen overnight and they don't always look like what you think they will. I'm a big believer in starting small and growing it until it makes sense to pivot.

One of THE biggest downsides/risks in being a solo-entrepreneur is illness. No one else can do my work for me. I have deadlines I can't just hand off. So even when I'm sick I can't just take 1 week off in the middle of everything going on (well, I guess I could I would just make a lot of clients and customers unhappy which is bad for business). To combat this I usually try to stay a few days ahead of my work and deadlines. Right now, I feel horrible. I am about 2 days ahead of all my work so I'm going to just touch on a few things before I go rest for the rest of the day. This is something you should consider before starting your own business!

(Ignore my face) because I'm releasing a new 2026 FREE Data Analyst Bootcamp on YouTube next Week!! I created the first ever Data Analyst Bootcamp about 3 years ago and millions of people have taken it. Since then, I've created a lot more content and I wanted to update it. Here's what it already included: 1. MySQL 2. Excel 3. Tableau 4. Power BI 5. Python 6. Pandas 7. Building a Portfolio Website 8. Creating a Resume 9. Practicing for Technical Interviews 10. Azure 11. AWS 12. How to use LinkedIn to Land a Job New Content Being Added: 13. R for Data Analysis Series 14. Git and GitHub Series 15. Data Fundamentals Series 16. Databricks for Beginners Series 17. ETL in Databricks Series This will be the longest free Data Analyst Bootcamp in the world (clocking in at around 29 hours). It took 3 hours just to download it! I'm super excited and hope it'll continue to be extremely helpful to everyone out there trying to learn data skills!

In 2022, my YouTube channel was growing and I had about 100k subscribers. I had tons of people reaching out wanting me to mentor them... so I started a Mentorship side business! It was fairly simple. I took on 5 people at a time and mentored them 1-2 times per month and charged 75$ per month. It was really successful and lots of people got jobs within the first 3 months I worked with them. I felt like it was well worth the money so I finally started advertising it and my backlog started growing. First to 50 people, then 100, 250, 500, and eventually over 1000 people. I felt terrible that I knew I would never get to 99% of those people because there were just too many people. This was the main thing that drove me to create AnalystBuilder.com! What I wanted to do was create a platform where all 1000 of those people could go and be mentored by me - and make it cheaper. So I did just that, I got a team together and started building it out. To many, it may look like just another course platform (and I get that), but if you take the courses, I go a lot deeper than just how to use the tools. I try to go in-depth to talk about how to actually implement the tools, my thought processes on when to use one tool vs another, and tips and tricks I've never seen other courses talk about. We are almost 3 years into Analyst Builder and we've had over 150k people use the platform! Analyst Builder is an amazing platform to learn, not just as a beginner, but also if you're already a data professional looking to level up your career and get more in-depth guidance from me. I didn't set out to build Analyst Builder in the beginning, it just became a necessity over time. Thank you to everyone who has used/is using the platform and I hope you try it out if you haven't!

"I got laid off from my [Healthcare/Finance/other domain] job and want to break into data. Where do I start?" I get this DM just about every week and here's what I tell them: 1. If you have experience in a domain, use that! That's what's going to differentiate you from everyone else. 2. Focus on building data skills - start with Excel, SQL, Power BI, and AWS/Azure 3. Build a Project after you learn each skill using real data 4. Build a Portfolio with those projects and add your portfolio link to your resume 5. Target companies in your Domain that would value your experience and start applying 6. Reach out to Recruiters for those companies If you do that, you'll be ahead of most people applying for similar jobs - your domain experience will be a big selling point! Combine that with technical skills and you set yourself up well.

In this weeks video I'm reviewing the Google's AI Professional Certificate - I took this over the past few weeks and wanted to give an in-depth review of the certificate as whole and if it was worth taking. youtube.com/watch?v=TCUcxp…

I've been consulting in the data space for about 4 years now. Here are 5 things I've learned that I thought was really interesting: 1. 90% of clients actually do know what they want - just not how to execute it effectively 2. Managing Expectations is half the battle - delivering is the other half 3. Small customers are 5x the work of larger customers and pay half as much 4. Doing good work and getting repeat customers is hard, but the best way to sustain long term growth 5. Project creep happens with almost every project, addressing it and not giving into it should be the norm

Sharing some of the reasons I switched to Mac after 10 years of using PC. I'll make some videos upcoming comparing Microsoft OS and Mac OS. youtube.com/watch?v=o2ehgG…

Me today: kids these days won't be able to do anything because they'll rely on AI. My mom: those kids won't have jobs because of those computers! My grandma: kids won't learn math because of those calculators! My great-great-great-great grandma: those kids won't learn to make fire because of this flint... we used sticks!

According to everyone on X, 95% of workplaces are "toxic" I disagree. Toxic is not: - Your manager giving you hard feedback - Being told your work needs to be redone - Having to stay late on a deadline - A coworker who disagrees with you in a meeting - Not getting a 2 hour lunch break Toxic is: - Being yelled at or belittled - Credit for your work going to someone else, repeatedly - Retaliation when you raise concerns - Goalposts that move every time you hit them - Leadership that lies to your face Not everything is Toxic. Calling normal workplace friction "toxic" makes it harder to recognize and call out the real thing when it shows up.

@ezekiel_aleke not sure if I should tweet rt or not - thanks for the shoutout :)

he explained data analysis like no one else could. Retweet if you love him.

“I can’t wait to work on real data at a big company that’s clean and stored well” One of the highest hopes and the biggest letdowns you’ll have in your data career. It doesn’t get better with bigger companies. The data just gets larger and is stored in different systems.

The year is 2130. AGI has been achieved. Gerald, my granddaughters family robot, screams out. They rush in asking, “what’s wrong??” Gerald says his Excel formula references were changed and broke his spreadsheet. Nothing has changed.

A funny thing I’ve found is that the higher paying the job the more freedom they give you. Low paying jobs pay you less for a few reasons: 1. They don't have the money to pay you a reasonable wage 2. The role is easily replaceable 3. They are stingy and want to maximize value So they'll track every minute, police breaks, watch attendance like a hawk, and measure productivity daily. Higher paying jobs can sometimes do this, but more often it's the opposite. You'll get more freedom because: 1. They're trusting you to be the expert. 2. They're paying for you judgment and not labor 3. They care more about the outcomes rather than staying busy I've worked and consulted for every kind of company - big, small, startup, Fortune 500, big tech - almost always, the ones that pay more are more relaxed because they're trusting me to do what they paid me to do.