Learning data analytics in public has taught me something deeper than Excel or SQL. ๐
You can start from somewhere completely different and still build something meaningful.
I studied Animal Science.
I taught in classrooms.
I worked in customer service and sales.
Now, I'm learning data analytics.
And honestly, starting over isn't always easy.
There are days when you feel behind.
Days when you wonder if you're learning fast enough.
Days when the people around you seem miles ahead.
But I'm learning that progress doesn't require you to have everything figured out.
It starts with asking better questions.
1. Start with the question, not the tool.
Before opening Excel, ask:
What decision will this analysis help someone make?
2. Understand your data.
Where did it come from?
What does it leave out?
Can you trust it?
3. Learn the fundamentals.
Tools will change.
AI will get better.
But the ability to think clearly will always matter.
4. Learn to communicate.
Finding an insight is one thing.
Explaining it clearly enough for someone to act on it is another.
5. Build by solving real problems.
Don't just learn formulas.
Don't just watch tutorials.
Take a messy problem.
Work through it.
Make mistakes.
Figure it out.
Share what you learned.
AI can write a formula or SQL query in seconds.
But knowing what to ask, what to investigate, and what the answer actually means is the skill I'm building.
I'm Obinna.
I'm learning data analytics in public, one real problem at a time.
If you're learning a new skill, changing careers, or starting over too, you're not alone.
We're building from where we are.
What are you currently learning that could change your career?
@onyekanwelue Thereโs some truth in this. At the end of the day, youโre the one who has to live with the consequences of your financial decisions. Listen to advice, but donโt hand over that decision to other people.
A good product really does make selling easier. When people can see that it solves a real problem for them, you donโt have to work so hard to convince them.
If you build a great product:
โข It's easier to get customers
โข It's easier to keep customers
โข It's easier to make customers happy
The better the product, the less you have to convince people.
Make it so good people feel stupid for not getting it sooner.
You don't need to have your entire life figured out this Monday morning.
Just know what needs to be done today.
Then do it.
One good week can change a lot.
Hereโs a data skill I think more analysts need to take seriously:
Build an audit trail for your analysis.
If an AI tool, dashboard, or SQL query gives you an important business number, don't stop at the number.
You should be able to answer:
Where did this data come from?
What transformations happened?
Which rules or calculations were applied?
Who changed the data?
Can another analyst reproduce the result?
This matters because AI is making it easier to produce analysis at scale.
But when analysis becomes faster, mistakes can scale faster too.
A strong analyst doesn't just produce an answer.
They make the answer traceable, reproducible, and explainable.
That's the kind of analytics I want to keep learning and teaching.
Because when you work with data that affects people's decisions, accuracy is a responsibility.
The interview question "where do you see yourself in 5 years" and my brain immediately buffering like a bad wifi connection when he said he would be at my position.
๐ That โown emergency contactโ part is too real. Independence comes with freedom, but it also comes with a lot of responsibility you canโt pass to anyone else.
I deliberately donโt want to use AI to automate everything I do.
So I donโt become dumb and uselessโฆ๐คฃ๐คฃ๐คฃ๐คฃ
I still do few things manually, so I can at least take credit that I contributed to the project.
What an AI time to be alive.
Building a founder-led business:
Trust is 80% consistency, 20% talent.
Leads are 80% distribution, 20% offer.
Margin is 80% deletion, 20% pricing.
Freedom is 80% systems, 20% headcount.
Work the 80.
This is so real. Remote work can be great, but after a while you start missing those random conversations and just being around people. You really have to make an effort to stay connected.
Remote work can be lonely.
No colleague beside you.
No office gist.
No random โHave you eaten?โ ๐
If you work remotely long-term, create a routine that keeps you connected.
Talk to colleagues.
Join professional communities.
Leave the house sometimes.
Working from home shouldn't mean living in isolation.
That part about access to the right knowledge is so important. A lot of young people are curious and willing to learn; sometimes they just need exposure to whatโs possible and a chance to explore it.
Still reflecting on such an amazing experience in Ebonyi @ebonyiskillssummit.
I had the opportunity to speak with young people, students, entrepreneurs, and innovators about Al, the changing world of work, and the skills we need to stay relevant in this new era.
What stood out to me the most was the energy in the room, the questions, the curiosity, and the willingness to learn and explore what is possible with technology.
Al is moving fast, and I truly believe conversations like these are important because access to the right knowledge can open doors to opportunities people may not even know exist yet.
Grateful to have been part of this conversation and to have shared a little of what I know.
The part about judgment really stands out. AI can handle a lot of the heavy lifting, but understanding the problem and knowing what to do with the output is where the real value comes in.
Considering a career in Tech? Anything that has to do with number crunching will never be completely replaced by AI -- Finance, Data Analysis, etc.
If you're also a creative, AI will enable your work in UI/UX, Motion Design. AI output will never be up to par in these areas.
Let's talk about the part of data analytics people don't discuss enough:
Who should be accountable when an important business number is wrong?
The analyst who reported it?
The team that produced the data?
The person who defined the metric?
The manager who made the decision?
Or should accountability be shared?
With AI becoming more involved in analytics, who owns the final responsibility for a decision made from an AI-generated insight?
What do you think? ๐
This is the part people underestimate: focused practice compounds. You donโt need to master everything; you need to stay with one valuable skill long enough for your effort to become undeniable.
Most people underestimate what 1,000 focused hours can do. Put them into one valuable skill instead of scattering them across entertainment, distractions, and endless consumption. You'll barely recognize yourself afterward.
I get the point. Sometimes you really do need to lock in and give something your full attention, but I donโt think you have to completely disappear from everyone to succeed. Work hard, but donโt burn yourself out in the process.
The most successful period of my life came from just locking myself in a room and working for 12 to 16 hours straight.
No friends, no family, just me and a laptop.
Doable for most? No.
Necessary for most? Yes.
Sounds sad asf, but the truth is, this is what it takes.
Honestly, you can do everything right, get the job, and still have immigration become the problem. Being qualified is one thing; actually being allowed to work there is another. This is why you need God in the beginning God! and at the end God! There's nothing he cannot do! Always remember spiritual controls the physical! ๐ซ
Imagine passing the interview; the company likes you, and you can do the jobโฆ
Then immigration enters the group chat, and suddenly you're too expensive to hire. ๐ญ
Being qualified abroad is really only half the battle.