Day 26/30— Before & After
My data analytics journey isn’t ❌ Beginner → Expert
It’s
Confused → Practice → Mistake → Research → Fix → Understanding → Repeat.
And honestly
I’m enjoying the process. 🚀
Day 25/30 😂— Mistake
One of my biggest lessons in data analytics, don’t trust your first result.
Check the data.
Check the calculation.
Check the filter.
Check the data model.
Sometimes the problem isn’t DAX.
It’s me. 😂
Yesterday, we officially welcomed our new members into The DataElite. 🎉
We laughed, we introduced ourselves, we shared the story of how this community began, and we reminded each other of why we're here which is to build real skill, and to make sure the right people see it.
This is more than a group of data analysts. It's a family that happens to love data.
Today, we begin.
📌 Month 1 Theme: Professional Presence
Over the next four weeks, every member will rebuild how they show up online, from LinkedIn and X to a portfolio website and GitHub, so that when someone searches for a data analyst, our members are easy to find and impossible to overlook.
Week 1 starts now: LinkedIn, rebuilt.
To everyone who joined us yesterday, welcome. To everyone following along, watch this space.
@AgheMarvel83922@StephanieN67260 @SlimTallboi @BIwith_mina
#TheDataElite #DataAnalytics #ProfessionalPresence #NigerianAnalysts #DataCommunity
Day 24/30 — Analyst Skills
A good data analyst needs more than technical skills.
📊 Excel
🗄️ SQL
📈 Power BI
But also:
🧠 Critical thinking
🗣️ Communication
📖 Storytelling
💼 Business understanding
Tools get you started. Thinking takes you further
Want to be financially free by 2036?
Start now.
— Cut unnecessary expenses
— Build multiple income streams
— Invest aggressively & consistently
— Own scalable assets
— Stay disciplined
Compound effort + time = freedom
Your future self will thank you.
Here’s how I would do it if I needed to,
🚀 Step-by-Step Plan to Financial Freedom by 2036
1. Define What Financial Freedom Means to You
•Is it passive income covering expenses?
•A specific net worth goal (e.g., $1M)?
•No debt and full ownership of assets?
2. Know Your Numbers
•Track current income, expenses, debts, and assets.
•Set a clear target (e.g., $10M in assets or ₦5M monthly passive income).
•Use a financial tracker or spreadsheet.
3. Build Multiple Streams of Income
•Primary Job/Business: Maximize your main source first.
•Side Hustles: Freelancing, consulting, content creation.
•Digital Assets: E-books, courses, affiliate marketing.
•Rental Income: Real estate or shortlets.
•Stock Dividends & Crypto Staking: Start small and compound.
4. Live Below Your Means
•Delay gratification.
•Avoid lifestyle inflation.
•Budget and set monthly savings/investment targets (20–50% of income if possible).
5. Invest Aggressively, Consistently and Smartly
•Stocks/ETFs: Dollar-cost average into strong assets.
•Real Estate: Income-generating property.
•Crypto: Allocate a % for long-term plays (e.g., BTC, ETH, and staking).
•Private Equity: Invest in small businesses or startups.
Compound interest and asset appreciation will do the heavy lifting over a decade.
Day 23 — Portfolio
Day 23/30 🐙
I’m learning that a portfolio shouldn’t just say I created a dashboard.
It should show:
🎯 Business problem
🧹 Data preparation
📊 Analysis
💡 Insights
🚀 Recommendations
Don’t just show the dashboard. Show your thinking.
Day 22 — Projects
Day 22/30 🚀
Watching tutorials feels productive,Building projects feels different 😂
That’s where you discover Wait… why doesn’t this work?
And that’s actually where the learning begins
Build. Break. Fix. Learn. Repeat.
@Cyndi_analytics Seeing how people are using Ai with Data analysis now make me question myself if I’m dull or what ? I still don’t know how this work honestly .
Anyways good job 👏
Day 20/30📖— Data Storytelling
Data storytelling is turning Sales increased by 18% into:
Sales increased 18%, driven primarily by higher demand for our top-performing products
Numbers inform.
Stories make people care
Day 19/30 📅— Seasonality
Imagine your sales:
📈 November — Peak
📉 December — Decline
The obvious question isn’t:
Why did December fall? Ask
What happened in November that made sales unusually high?
Good analysis investigates the story behind the pattern.
One month into my first Data Analyst role, and I’ve been reflecting on the journey that led me here.
For anyone currently looking for their first analyst job, here are a few things I’d say:
• Know your Excel, Power BI and SQL fundamentals
• Have 2–3 projects you can confidently explain
• Understand the business problem behind your analysis
• Practice talking through your thought process
• Be ready for practical tasks, not just theory
• Know your CV and projects well because interviewers will ask about them
• Don’t stop applying while you’re still learning
• And please, don’t let rejection convince you that you’re not good enough.
You might get several “we’ll get back to you” before you get the one that changes everything.
Keep learning. Keep applying. Keep showing up.
Day 18/30 💰— Revenue
Revenue tells you how much money came in.
But revenue doesn’t automatically mean:
“The business is profitable.”
Always ask:
Revenue?
Costs?
Profit?
Margin?
Because high sales + terrible margins = an expensive celebration. 😂
Day 17/30 — Customer Analysis
4,000 customers.
25,900 orders.
At first glance, you might think 🤔 Wow lots of customers, But data analysis makes you ask:
Are customers returning?
How frequently do they purchase?
What’s the AOV ?
The number is only the beginning of the story.
Day 16/30 📊— KPI
A KPI isn’t just a number.
Revenue = $9.7M sounds impressive.
But then you ask:
❓ Compared to what?
❓ Is it growing?
❓ What’s the profit?
❓ Which customers generated it?
❓ Which products drove it?
Context turns numbers into insight.
🔥 DATA ANALYTICS IN 2026 — MORE THAN JUST DASHBOARDS 📊
Most beginners think Data Analytics is only about creating charts in Excel or Power BI.
But the real industry demand is much bigger.
A skilled Data Analyst should know how to :
#PowerBI