@m_jnr1@grudy_smith Letโs know this. Mr. Tieku of Star Oil, is the CEO. The board and private owners are the ones making such decisions.
William Tewiah of ZEN is the founder and managing director.
๐ด ๐ฐ๐ผ๐ต๐ผ๐ฟ๐๐. ๐ฎ๐ฌ๐ฌ+ ๐ฎ๐ป๐ฎ๐น๐๐๐๐.
๐ข๐ป๐ฒ ๐๐๐๐ฑ๐ฒ๐ป๐ ๐ฒ๐บ๐ฝ๐น๐ผ๐๐ฒ๐ฑ ๐ถ๐ป ๐ฑ ๐๐ฒ๐ฒ๐ธ๐ ๐๐ถ๐๐ต ๐๐ฒ๏ฟฝ๏ฟฝ๐ผ ๐ฝ๐ฟ๐ถ๐ผ๐ฟ ๐๐ธ๐ถ๐น๐น๐.
๐๐ผ๐ต๐ผ๐ฟ๐ ๐ต ๐ถ๐ ๐ผ๐ฝ๐ฒ๐ป.
Most programs teach you tools.
This one teaches you how to use them โ with AI as part of your workflow, not an afterthought.
Thatโs the gap.
๐ช๐ต๐ฎ๐ ๐๐ผ๐โ๐น๐น ๐น๐ฒ๐ฎ๐ฟ๐ป:
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โ Statistics, Figma, PowerPoint
โ ChatGPT & Claude โ used the way real analysts actually work
๐ช๐ต๐ฎ๐ ๐๐ผ๐ ๐น๐ฒ๐ฎ๐๐ฒ ๐๐ถ๐๐ต:
โ 8+ real projects you can show
โ 1-on-1 mentorship from start to finish
โ A way of working that shows up clearly in your output
Start: June 25
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โฆ89,999 (Local) / $89.99 (International)
50 seats.
The people who take this seriously now
are the ones with options later.
Register ๐
https://t.co/CuWAr3lKo1
Who do you know that should see this?
#Datafam
Havenโt used power BI in 3 months and decided to explore the changes today ..
Particularly Claude AI power bi integration via MCPโฆ
And boy oh boy, this is mind blowing, i tried to do something that took me 4 hours in 9 minutes..
Iโll play with this more and make a video soon
#Datafam
๐ง๐ต๐ฒ ๐ถ๐บ๐ฎ๐ด๐ฒ ๐ผ๐ป ๐๐ต๐ฒ ๐น๐ฒ๐ณ๐ ๐๐ฎ๐ ๐บ๐ ๐๐ฒ๐๐๐ฝ ๐ฎ๐ ๐๐ต๐ฒ ๐ฒ๐ป๐ฑ ๐ผ๐ณ ๐ฎ๐ฌ๐ฎ๐ฏ.
Learning data analytics.
Earning โฆ30k per month.
The one on the right is my current setup.
Iโm sharing this not to flex. But to encourage you.
Have I gotten to where I envisioned? No.
Did I fail multiple times? Yes.
Did I win? Absolutely.
Success isnโt linear.
There were months I didnโt know how Iโd pay bills. Projects that went nowhere. Clients who ghosted. Opportunities that fell through.
But I kept learning. I kept building. I kept showing up.
And things started compounding.
One skill led to another. One project led to the next. One person I helped came back with someone else who needed help.
It wasnโt dramatic. It was gradual.
But it was real.
Hereโs what I learned:
Everything compounds.
The SQL you learn today might not pay off for 6 months. But when it does, it pays.
The portfolio project you build when no oneโs watching? Someone will see it eventually.
The person you help for free? They might become your biggest advocate.
Nothing is wasted.
Hardwork pays. But smart work pays faster.
I worked hard in 2023. But I didnโt work smart.
I was learning everything. Building nothing specific. Chasing every opportunity.
Now I focus. I build in public. I teach what I learn. I help people solve real problems.
That shift changed everything.
Donโt give up.
I know itโs hard. I know it feels like everyone else is moving faster. I know the rejections hurt.
But keep going.
Learn every day. Build every day. Pray every day.
Success is inevitable if you donโt quit.
Iโm still on this journey. I havenโt arrived. But Iโm not where I was.
And neither will you be if you keep moving.
One step at a time.
#DataAnalytics #Datafam
๐ ๐๐ผ๐ฟ๐ธ๐ฒ๐ฑ ๐๐ถ๐๐ต ๐ฎ ๐๐๐๐ฑ๐ฒ๐ป๐ ๐ผ๐ป ๐ฎ ๐๐บ๐ฎ๐น๐น ๐ฎ๐ป๐ฎ๐น๐๐๐ถ๐ฐ๐ ๐ฝ๐ฟ๐ผ๐ท๐ฒ๐ฐ๐.
It turned into a surprisingly realistic case study.
The problem:
International students sign up for German health insurance months before arriving.
Then visa delays happen.
Payment issues happen.
Students switch providers.
And insurers are left with hidden operational and financial risk they canโt see coming.
So we built a dashboard to answer one question:
Where is the risk actually coming from?
๐ง๐๐ ๐๐๐ง๐
We simulated ~5,000 student records and analyzed:
โ Early churn behavior
โ Debt accumulation before arrival
โ Payment failures (SEPA vs bank transfer)
โ Visa outcomes and inactive accounts
โ Cost shock segments (age + employment)
โ Geographic concentration of risk
Real scenarios.
Messy data.
Actual business problems.
๐ช๐๐๐ง ๐ช๐ ๐๐ข๐จ๐ก๐
โ Early churn happens fast โ average around month 3
โ Arrival delays dramatically increase debt exposure
โ Payment failures strongly correlate with churn risk
โ A small group of segments drives most cancellations
These arenโt abstract insights.
These are operational red flags.
๐ง๐๐ ๐๐๐ฆ๐๐๐ข๐๐ฅ๐
Built entirely in Excel using:
โ Power Pivot measures
โ Pivot-driven KPI cards
โ Segmentation analysis
โ Behavioral and operational risk drivers
Page 1: Financial exposure (debt, churn losses, operational cost)
Page 2: Drivers of churn and risk (payment behavior, visa outcomes, delay buckets, nationality clusters)
No fancy tools.
Just Excel and clean thinking.
๐ช๐๐ฌ ๐ง๐๐๐ฆ ๐ ๐๐ง๐ง๐๐ฅ๐ฆ
The goal wasnโt flashy visuals.
It was building something that could realistically be presented to an insurance operations team.
Something that answers:
โWhere do we lose money?โ
and
โWhich customers are high-risk?โ
This is what real analytics looks like.
You donโt need Tableau or Python for every project.
You need to understand the problem and connect the data to business decisions.
Sometimes the most interesting analytics projects arenโt about complex models.
Theyโre about making hidden risk visible.
#DataAnalytics #Excel #BusinessIntelligence #Datafam
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These roles are required for a start-up Bulk Distribution Company (BDC - Oil & Gas) sector.
- Head of Commercial
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