Mo Chen

My newsletter is back 📣 Sign up and get my one-page checklist on how I pressure-test AI: the 5 questions I run on any output before I trust it. It's the first thing you get when you join.

Link here: mochen.io/newsletter/

Emails on using AI to do real work, the kind that holds up when someone asks how you got the answer. For people advancing a data career or putting AI to work at their job. No prompt hacks and no hype, just the workflows that actually work and the judgment to know when to trust them.

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13 hours ago | [YT] | 16

Mo Chen

Another day, another demo of someone building an app with AI that solves absolutely nothing.

A to-do list. A weather widget. A "SaaS in 20 minutes" that has no users and was never meant to have any. Built purely because you can, not because anyone needed it.

That's most AI content right now. Impressive to watch. Useless the second the video ends.

And it's quietly teaching people the wrong lesson. They see the flashy build, assume that's what "good at AI" looks like, then point AI at their hardest, rarest task on day one. They get a mediocre result and write the whole thing off as overhyped.

The gap very few people are filling is the practical one. Not "what cool thing can AI build?" but "what problem do I actually have that AI can take off my plate today?"

Because the real wins are boring.

Drafting the emails you send 20 times a week. Summarizing the meeting you half-listened to. Turning messy notes into something readable. First drafts of anything. Dull, constant, and that frequency is the entire point. Automate something you do every day and you get back real hours. Build a to-do app you'll never open... I'm not sure how useful that is.

Most knowledge workers already use AI at work. Very few are using it on the stuff that actually moves the needle.

So before the next "look what I built" post pulls you in, ask the only question that matters: does this solve a real problem I have, or is it just using AI to create something that has no purpose and no use whatsoever?

Be honest. The last thing you made AI do, was it solving an actual problem, or were you just seeing if you could?

2 days ago | [YT] | 29

Mo Chen

Do you currently use AI in your data analysis workflow? If you have any specific use cases or any reasons why you have not used it at all, comment 👇

1 month ago | [YT] | 11

Mo Chen

🔉 Something big is coming | SQL + Power BI Portfolio Project 📣

In this project
✅ we'll be cleaning and transforming data in the cloud using SQL queries
✅ connect to our BI-ready dataset in the cloud in Power BI to build our report

I hope you're looking forward to it!

3 months ago | [YT] | 438

Mo Chen

My happy place 😃

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3 months ago | [YT] | 146

Mo Chen

Will AI Replace Data Analysts / Scientists / Engineers?

...

My short answer is NO.

AI won't replace data analysts, it will redefine them.

The same goes for other similar data roles such as data scientists or data engineers.

On top of this, the use of AI will and is already creating new roles such as AI governance managers, AI practitioners, AI framework managers, etc.

Change is normal.

It is human nature to feel anxious about change which is probably why 'Will AI replace data analysts?' is one of the top questions I still get asked, well over 3 years since the big hype around the rollout of ChatGPT.

To put it very simply - AI won't take your job. People who know how to use AI will.

I see the use of AI tools and products as just another skillset to learn.

Imagine this scenario:

You're a hiring manager looking to fill an analyst role that involves lots of data analysis.

Who would you rather hire?

a) the person who barely knows what to do with a dataset, how to perform initial quality checks, has not got a clue how to gather requirements around what insights to build that can actually drive business impact AND can use AI very well (i.e. great at prompting)

OR

b) the person who has strong data analysis foundations, knows exactly what to do initially with a dataset, how to perform quality checks, knows how to gather the right requirements from the right SMEs to build insights that drive business actions AND can use AI very well (i.e. great at prompting)

...
...
...

I hope your answer is b. If it isn't, you should probably unsubscribe now.

If you have strengths AI can't match - I define these as a mixture of common sense, intelligence, thinking for yourself and taking the initiative - then you probably already are tackling complex, unpredictable questions requiring business context, like multi-dimensional issues without clear decision trees.

And if you're already doing this, then AI is not something you need to worry about when it comes to your job security.

I strongly encourage you to embrace AI tools, products and services to boost not just your data analysis workflow, but workflow in general.

Comment below what your top AI use case are right now.

3 months ago | [YT] | 233

Mo Chen

I was going to make a more personal video along the lines of 'Data Analyst in the Countryside'. Would you even be interested? Vote 👇

3 months ago | [YT] | 27

Mo Chen

🔊 MY FREE NEWSLETTER IS BACK 📣 SIGN UP HERE 👉 mochen.info/ (you have to scroll down a little) and don't forget to complete the double opt-in to receive ACTIONABLE TIPS & ADVICE ON HOW TO

✅ Build a professional data portfolio
✅ Create projects that tackle real-life business problems
✅ Write a resume that will actually get you interviews
✅ Learn only technical skills that you will genuinely use on the job
✅ Build a data career to live the life you want to

Have a nice day!

3 months ago (edited) | [YT] | 39

Mo Chen

I think Google just quietly launched one of the most useful AI courses on the internet.

If you’ve been following my content for a while, you’ll know I’m not a fan of fluffy, 40‑hour courses that leave you with a badge but no actual skills you can use at work.

This new Google AI Professional Certificate on Coursera feels different.

It’s built around how we actually work day to day, and it walks you through using AI across the whole workflow, not just for cute prompts or writing emails.

Here’s what it covers:

🧠 AI Fundamentals – understand how AI works, how to prompt properly, and how to use it responsibly at work.

💡 AI for Brainstorming and Planning – turn vague ideas into structured project plans and timelines.

🔍 AI for Research and Insights – use tools like Gemini and NotebookLM to dig through sources and pull out serious insights fast.

✍️ AI for Writing and Communicating – draft emails, reports and stakeholder updates, then adapt them to different audiences.

🎨 AI for Content Creation – generate images, videos and presentations so your ideas don’t get stuck at “rough draft” stage.

📊 AI for Data Analysis – clean messy data, build formulas and visualise trends using natural language in Sheets.

💻 AI for App Building (Capstone) – use “vibe coding” to build your own AI-powered app without writing code, and automate annoying repetitive tasks.

Why I think this matters if you’re into data and analytics:

Most of you who follow me either want to become data analysts or you’re already working with data.

The next wave of “strong analysts” won’t just be good at SQL, dashboards and storytelling – they’ll be the ones who can plug AI into every part of their workflow: research, scoping, analysis, comms, even light app building.

This certificate is basically a structured way to become that AI‑powered analyst: someone who can use AI as a collaborator to speed up the boring bits and spend more time on thinking, context and decisions.

If you’ve been meaning to “get serious about AI” but didn’t know where to start (or which of the 10,000 random courses to pick), this one is a good starting point.

Here’s the link if you want to check it out and maybe start building proper AI skills:

imp.i384100.net/WODvnJ

If you do end up checking this certificate out or even enrolling, comment below which part you’re most excited about: AI for analysis, content, or app building?

3 months ago | [YT] | 118

Mo Chen

🎯 If you’re learning Tableau, your first real challenge isn’t the tool — it’s the project.

Most beginners get stuck after following a few tutorials. They can make charts… but don’t know how to turn data into a dashboard that feels real.

That’s exactly why I built my new Tableau Customer Churn Dashboard Project.

It’s designed to help you
✅ create your own dashboard that tells a business story

You’ll learn how to:
✅ Work with user-defined parameters
✅ Combine advanced select and menu dashboard actions
✅ Design a professional Tableau dashboard that real-life stakeholders would actually use

This portfolio project course is a practical way to build something you can actually show in your portfolio in just UNDER 2 HOURS — and a way to support the free content I share across YouTube and LinkedIn.

💡 Think of it as a small investment that accelerates your learning journey.

👉 Get the project here:
www.udemy.com/course/tableau-portfolio-project-cus…

You don’t need to wait to “feel ready.” Build your first professional Tableau project today — and make it the piece your portfolio’s been missing.

4 months ago | [YT] | 132