AbdulQudus | Data Analyst retweeted
This lady clearly explains average, Median and Quartile in Data Analysis🔥
AbdulQudus | Data Analyst retweeted
And just like that…🥹my 3 months data analytics journey is coming to an end.
Classes completed ✅
Capstone completed ✅
So many lessons, struggles & “why is this not working?” moments 😂
I’m proud of how far I’ve come. This is only the beginning.
@ezekiel_aleke @TechSphereAcad
AbdulQudus | Data Analyst retweeted
SQL is just:
- Data Storage (Tables, Schemas, Databases)
- Data Cleaning (TRIM, REPLACE, CAST, COALESCE)
- Data Retrieval (SELECT, WHERE, ORDER BY, LIMIT)
- Data Analysis (GROUP BY, HAVING, JOINS, SUBQUERIES)
- Data Automation (Views, Stored Procedures, Triggers)
That’s it
AbdulQudus | Data Analyst retweeted
Data Cleaning Checklist:
- Check for Duplicate
- Identify missing values
- Correct datatype
- Standardize text values
- Validate data values
- Check for inconsistencies
- Check for outliers
- Document changes
Day 13/∞ 📊
Yesterday I was working with SUM and AVERAGE in Excel.
It’s funny how simple calculations start looking different when you’re thinking about them as tools for analysing actual data.
Still learning. Still connecting the dots. 🚶🏽♂️📊
AbdulQudus | Data Analyst retweeted
Power BI is just:
- Data Connection (Excel, SQL, Web, APIs)
- Data Cleaning (Power Query)
- Data Modeling (Relationships, Star Schema, DAX)
- Data Visualization (Dashboards, Charts, Filters)
- Data Sharing (Publish, Power BI Service, Reports)
Don't complicate it🥀
AbdulQudus | Data Analyst retweeted
Dear Data Analyst!
If you start today
You can learn Excel in October
Learn Power BI or Tableau in November
Learn SQL in December
Start applying for jobs in December
Just 3 months is all you need
Start now and learn consistently❤️
Day 12/∞ 📊
Today I learned two Excel functions I’m definitely going to be using a lot: SUM and AVERAGE.
Being able to quickly total a range of data and find its average already makes Excel feel way more useful.
Small step, but we move. 🚶🏽♂️
Day 11/∞ 📊
Continuing with Excel today.
I’m getting into how data is structured within a worksheet — cells, cell references and how to locate specific data.
The basics are starting to connect. 👀
We move. 🚶🏽♂️📊
AbdulQudus | Data Analyst retweeted
Leave:
Excel
Power BI
SQL
Python
Portfolio
Cv
Job
How to build your online visibility
To me
You just bring:
Listening hears
Consistency
Patience
3 months
A laptop
Data Sub
We lock-in 8 days❤️🔥
Don’t miss this for anything
AbdulQudus | Data Analyst retweeted
I made an ebook.
I spent a lot of time talking to and interviewing experts in cybersecurity, tech sales expert. in conjunction with a fintech brand, to bring this e-book to life.
It’s completely FREE.
Take it, share it with your friends and family, and give someone who needs it a roadmap to break into tech and start earning in dollars.
1. drive.google.com/file/d/1NVF…
2. drive.google.com/file/d/1QW0…
Day 10/∞ 📊
Today was another Excel basics day.
Workbook, worksheet, rows, columns… and now I’m getting into cells.
The more I learn, the more I realize there’s a lot to this thing 😂
We move. 🚶🏽♂️📊
Today I learned the difference between a workbook and a worksheet in Excel.
Workbook = the whole Excel file.
Worksheet = a sheet inside it.
Simple? Yes 😂
But I’m learning not to skip the basics.
AbdulQudus | Data Analyst retweeted
I didn’t have the “right” background.
I just refused to stay where I was.
You don’t need the perfect starting point.
You only need the decision that this is no longer acceptable.
AbdulQudus | Data Analyst retweeted
Tutorial datasets are clean.
Real-world data?
Missing values,
Duplicates,
Wrong formats,
Inconsistent entries,
And sometimes… pure chaos😂
That's why practicing with messy datasets is so important.
The goal isn't just to learn the tool. Learn how to handle the problem📊.
AbdulQudus | Data Analyst retweeted
DATA MODELING
Putting data into tables is easy.
Designing those tables so people can actually understand and use the data is the real challenge.
That’s where Data Modeling comes in.
It defines how data is structured and how different pieces of data relate to each other.
Three common levels:
→ Conceptual: What exists?
→ Logical: How is it connected?
→ Physical: How will it be stored?
Real-world example:
An e-commerce business has:
Customer → Order → Product → Payment
Instead of throwing everything into one giant table, engineers carefully organize these relationships.
For analytics, the same data might become:
Fact Sales + Customer + Product + Date
Good data modeling makes:
→ Queries easier
→ Definitions clearer
→ Reports more reliable
→ Data easier to maintain
Free resources:
→ dbt SQL Models
lnkd.in/g5WGRhdw
→ Kimball Group
lnkd.in/gjrHJZeN
Good data modeling turns complex data into something people can actually use.












