Mo Chen

Just a quick note that this is your last chance to grab a bargain deal on your Datacamp subscription ➡️ 55% OFF UNLIMITED LEARNING ❗️

You know it has been my go-to platform for learning data skills for years now as I prefer hands-on, applicable learning (as opposed to watching endless tutorials).

You can browse the entire course catalog here: datacamp.pxf.io/qzJaYj

If I were you, I’d pick these courses and tracks:

Excel
Excel Fundamentals: datacamp.pxf.io/DyPv7o

SQL
SQL Fundamentals: datacamp.pxf.io/190vJa
Data Analyst in SQL: datacamp.pxf.io/GKeM7r

Power BI
Power BI Fundamentals: datacamp.pxf.io/POXM7X
Data Analyst in Power BI: datacamp.pxf.io/jek9Yv

Tableau
Data Analyst in Tableau: datacamp.pxf.io/raZmY5

Python
Python Data Fundamentals: datacamp.pxf.io/aOqM7b
Data Analyst in Python: datacamp.pxf.io/kOerYn

AI Native Courses
Introduction to AI for Work: datacamp.pxf.io/POXMPz
Introduction to SQL: datacamp.pxf.io/kOermz

1 week ago | [YT] | 28

Mo Chen

48 hours.
3 days.
1 week.

That's the time it takes to create a data project.

I've seen it all.

And all of these people came from different backgrounds:
| Career switchers ready to build their portfolio.
|| Learners tired of scattered, unfinished projects.
||| Anyone who wants structure and accountability.

What can you accomplish with what's left in 2025?

Start, for FREE, here:
mochen.info/3-projects-3-datasets-3-domains/

1 week ago | [YT] | 83

Mo Chen

It's amazing how much you can take from one quote.
Look at this:

"Looking at the query structures, views, and CTEs after CTEs, and queries based on business questions really taught me I need to step up my SQL and analytical skills".

Pause for a second here.

"Queries based on business questions".

I have always said this.

It doesn’t matter how great you are at writing queries if you don’t use them to solve real business problems.

But if you become a master of identifying problems that can be solved with data, you'll become unstoppable.

When you know what the goal is, all you need to do is work hard.
But if you don’t know your goal, hard work will not help you.

Here's the quickest way for you to understand what you can do with data:
mochen.info/50-projects-90-days/

1 week ago | [YT] | 46

Mo Chen

I know that most people who are willing to invest $550 in their education trust more in WHAT THEY SEE, rather than what they hear.

I also know they want to SEE people like them reaching their own goals using the same service.

What's the best way to know if these others are accomplishing OUR goals?

You wouldn't be active in a community that was literally wasting your time, money and effort, right?

If we share the same thought process, it's reasonable to assume that knowing how active members are in my community directly relates to its success.

Because:
| More engagement = More interest
| More interest = More commitment
| More commitment = More goals achieved
| More goals achieved = Better feedback
| Better feedback from people who are in the same situation as my target audience = More credibility

Makes sense?
For me, it does.
That's a simple way you can use data analytics to understand the "health" of your business.

See? No fancy tools, no dashboards. ONE METRIC.

As long as you know what you're doing, it really comes down to one thing: Working hard on the right things.

1 week ago | [YT] | 48

Mo Chen

📢 50% OFF UNLIMITED LEARNING 📣 DataCamp currently have their Black Friday offer on where you can get a 50% discount on all of their courses and tracks.

You know DataCamp has been my go-to platform for learning data skills for years now as I prefer hands-on, applicable learning (as opposed to watching endless tutorials).

You can browse the entire course catalog here: datacamp.pxf.io/qzJaYj

If I were you, I’d pick these courses and tracks:

Excel
Excel Fundamentals: datacamp.pxf.io/DyPv7o

SQL
SQL Fundamentals: datacamp.pxf.io/190vJa
Data Analyst in SQL: datacamp.pxf.io/GKeM7r

Power BI
Power BI Fundamentals: datacamp.pxf.io/POXM7X
Data Analyst in Power BI: datacamp.pxf.io/jek9Yv

Tableau
Data Analyst in Tableau: datacamp.pxf.io/raZmY5

Python
Python Data Fundamentals: datacamp.pxf.io/aOqM7b
Data Analyst in Python: datacamp.pxf.io/kOerYn

AI Native Courses
Introduction to AI for Work: datacamp.pxf.io/POXMPz
Introduction to SQL: datacamp.pxf.io/kOermz

2 weeks ago | [YT] | 75

Mo Chen

If you ever wondered what is like to live as a remote Data & Analytics Manager, I have some videos for you to watch:

Life of a Data Analyst in the UK
https://www.youtube.com/watch?v=JP-3E...

Day In The Life of a REMOTE DATA ANALYST
https://www.youtube.com/watch?v=sNF2o...

Remote Data Analyst (short)
https://www.youtube.com/watch?v=GXOgn...

Remote Data Analyst (short)
https://www.youtube.com/watch?v=GXOgn...

Remote Data Analyst (short)
https://www.youtube.com/watch?v=Rh7fA...

Data Analyst Life in a Rural Town
https://www.youtube.com/watch?v=3V_Dx...

And here's everything you need to start your Data Career:

How I built 50+ Data Projects in 90 days
mochen.info/50-projects-90-days

How to frame real data problems in Finance, Healthcare and Marketing
mochen.info/data-problem-framing

3 Projects. 3 datasets. 3 domains
mochen.info/3-projects-3-datasets-3-domains

2 weeks ago | [YT] | 181

Mo Chen

7 things I learned after 7 years as a Data & Analytics Manager that no course ever taught me:

1. Soft skills matter more than technical skills
Gathering requirements, managing stakeholders, and translating business needs into technical solutions? 70% of my day.

2. You'll spend more time in meetings than in Excel
Scrums, stakeholder alignment sessions, "cross-functional collaboration". The higher you go, the more your role becomes about coordination and communication.

3. Learning never stops
I thought I'd master a few tools and be set. Wrong.
New platforms, new methods, new frameworks. That's what you have to learn if you want to stay relevant.

4. Data cleaning is still the hardest part
Connecting to databases, handling inconsistent keys, facing multiple sources. I know it's fancier to speak about "building dashboards" but most technical work happens before you even open Tableau.

5. Your job is to make insights obvious.
Line charts and bar charts are my go-to for a reason. The easier your stakeholder understands the data, the faster they can make decisions. Fancy visuals without clarity or overwhelming your audience with 67 different charts is just ... well ... you know what it is.

6. You need to translate business requirements into technical solutions
When a stakeholder says "compare product sales by type", you know that means a line chart over time.
When they say "analyze customer churn by age and tenure", you're already thinking combo chart: bars for volume, line for churn rate.
You only learn this by doing real projects.

7. Portfolio projects need to mirror real work
Multiple data sources, unclear requirements, and stakeholders who change their minds halfway through.
Your portfolio should prove you can handle that.

If you're building your portfolio and want to work on projects that actually mirror what you might do in Finance, Healthcare, and Marketing (with real business questions, and real stakeholder scenarios)...

I've shared my entire framework on how to frame business problems:
mochen.info/data-problem-framing/

2 weeks ago | [YT] | 272

Mo Chen

I completely failed at learning Python (the first time).
Couldn't apply a single thing at work.

So, my take on learning is:
You can learn the "right" way and still learn the wrong things.

My first attempt at Python looked like this:
→ Took a popular course (I think it was by Corey Schafer)
→ Learned dictionaries, lists, loops, iterations
→ Built chess games and random number generators

I thought I understood the concepts, but then came the time when I sat down at work and tried to use Python ... and had ZERO idea how to actually analyze data with it.

My mistake was that I learned programming, and not data analysis (though, at the time, I didn't think there was much difference between them). But I soon came to realize that, while programming teaches you specifically how to code, data analysis teaches you how to solve business problems ... with data.

At that stage I had no idea how to:
→ Clean datasets
→ Transform data for analysis
→ Create visualizations

And so I quit. I simply gave up on Python completely. Until I tried again, with all the scary monsters in my head. I gave it another go, but changed my approach:

Instead of learning "everything about Python" I focused on one thing: Data analysis.

No web development, game development or software engineering. I just focused on learning four libraries:
→ Pandas (data manipulation)
→ NumPy (numerical operations)
→ Matplotlib (visualization)
→ Seaborn (visualization)

That's it. And you know what? It worked. I could finally apply it at work. And the more I applied, the better my learning was. It sounds like common sense, but, at the time, it was a path full of doubts and impostor syndrome.

So, here's my advice:
Don't try to learn everything:
Excel + SQL + Tableau + Power BI + Python + R + AWS + Azure...

And then end up mediocre at all of them.

Just have a goal (and make that goal to solve problems with data) and learn the tools as you go.

2 weeks ago | [YT] | 135

Mo Chen

Learn more in 3 days than in 3 years.
FREE -> mochen.info/3-projects-3-datasets-3-domains/

What you're going to explore in these projects:

-> Product affinity analysis
-> Identifying cross-sell opportunities
-> Creating Bundle recommendations based on purchase pattern
-> Price trend analysis
-> Comparing volatility
-> Correlation analysis
-> Time-series price normalization
-> CAGR and YoY trend analysis
-> Weighted averages
-> Outlier detection (IQR/Z-score) with small-n suppression checks

Try to build these projects yourself.
Use LLMs to explain what you don't know.

Learning is about deliberate action.
And nothing is more actionable than projects.

2 weeks ago | [YT] | 136

Mo Chen

🏃Running in the Lake District - no flats and no straights. Had to take a 2 minute breather at the top - what a view!

3 weeks ago | [YT] | 113