Power BI is an interactive data visualization and business intelligence tool developed by Microsoft. It’s part of the Microsoft Power Platform and brings together apps, services, and connectors that turn data from sources like databases, spreadsheets, PDFs, APIs, and cloud services into interactive reports and dashboards.
At the core of Power BI’s analytical power is Data Analysis Expressions (DAX)—a formula language used to create calculations, measures, and logic within data models. DAX helps analysts move beyond raw numbers to meaningful metrics that drive decisions.
The real value comes from how analysts work with messy data, model it properly, write smart DAX, and design dashboards that answer real business questions.
- Data Cleaning
In the real world, data is rarely clean.
You’ll see:
Missing values
Duplicate records
Inconsistent naming (e.g. “Nairobi”, “NRB”, “NBO”)
Dates in different formats
Numbers stored as text
Analysts use Power Query to handle this stage:
Removing duplicates
Standardizing formats
Splitting and merging columns
Creating calculated columns
Combining multiple data sources
This step is less about perfection and more about making data usable and reliable.
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Data Modeling
Once data is cleaned, analysts design a data model—usually a star schema.
Fact tables → transactions, sales, orders, events
Dimension tables → dates, customers, products, locations
Good modeling:
Reduces DAX complexity
Improves performance
Makes measures reusable
Prevents incorrect totals
Relationships, cardinality, and filter direction matter more than visuals at this stage. A clean model is what allows dashboards to scale.
3.** DAX**
DAX is where analysis happens.
Instead of just showing totals, analysts write measures like:
Revenue growth
Month-over-month change
Rolling averages
Conversion rates
Performance vs targets
Common DAX concepts include:
Measures vs calculated columns
Filter context vs row context
Time intelligence functions
CALCULATE, FILTER, ALL, VALUES
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Dashboards
A good dashboard doesn’t try to show everything.
It focuses on:
Key metrics
Trends over time
Comparisons
Exceptions and outliers
Analysts design dashboards around questions like:
What’s performing well?
What’s declining?
Where should attention go now?
Interactivity (filters, slicers, drill-throughs) allows users to explore data without overwhelming them.
- From Dashboard to Action
The final step is impact.
Power BI dashboards help teams:
Track KPIs in real time
Identify inefficiencies
Support operational decisions
Communicate insights clearly
When data is modeled correctly, DAX is intentional, and dashboards are focused, insights move from reports into decisions and action.What is your best part as an analyst using power bi for your analysis work ?
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