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In data analysis, which skill creates more impact?
A. Technical Mastery (Perfect SQL/Python)
B. Communication/Storytelling (Data to Decisions)
I vote B. The courage to communicate an imperfect finding is worth more than waiting for a perfect one.
What's your take? 👇
INNER JOIN moments: focus only on what matches your goals.
FULL JOIN moments: embrace everything and sort it out later.
You don’t need perfect timing or perfect clarity , just the courage to start connecting the dots.
Learning SQL JOINs taught me something deeper:
Growth isn’t about having all the answers.
It’s about connecting the pieces you already have — even when they don’t look complete.
Real data is messy, scattered, imperfect.
So is learning.
• They turn random tables into a real “story”
• They separate analysts who drag-and-drop from analysts who actually think
Great modeling isn’t about tools.
It’s about connections.
Understand the relationships → understand the model → solve the problem.
Relationships are the backbone of good modeling.
Forget fancy algorithms for a sec.
If you can’t understand how your tables relate, your model will confuse you more than it will help you.
Here’s the truth:
• Relationships reveal the real drivers
• They prevent wrong insights
Learnt Time Intelligence in DAX today, and honestly it’s all about the date table.
Functions like YTD, MTD, PY are fine.
It’s the setup that tests you: continuous? marked? relationship correct?
Fix that, and everything clicks.
What clicked first for you with Time Intelligence
Nothing prepares you for real dirty data.
You think it’s just missing values… until you meet:
• Dates in 5 different formats
• A yes/no column with 14 different ‘interpretations’
• Prices stored as ‘₦2000’, ‘2000NGN’, and ‘two thousand’
Just know your day is a long one 😭📊
I just transformed a single messy table into 9 well-structured tables and rebuilt the entire data model in Power BI.
Database normalization is one of the most underrated skills for data analysts.
Clean data = clean insights.
#DataAnalysis#PowerBI#SQL
4. It prevents duplicates, wrong joins, and misleading insights
It’s the foundation of strong Power BI data models and star schemas
Most analytics issues don’t come from the tools, they come from messy data.
If you want cleaner insights and smoother DAX, start with normalization.
Normalization is one of the most underrated skills in data analysis.
Here’s why every analyst should understand it:
1. Clean data starts with good structure
2. It makes analysis faster and easier
3. It trains you to think clearly about relationships