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Sales Performance Dashboard
Overview: This Power BI project provides a comprehensive Sales Performance Dashboard to help businesses monitor and analyze key sales metrics. The dashboard consolidates raw sales data into interactive visualizations, enabling decision-makers to track revenue, product performance, and regional sales trends in real time.
Nice integration of pricing, cancellations, and revenue trends.
Did you model this using a star schema or a flat transactional table? I’ve found forecasting accuracy shifts significantly depending on how booking and cancellation events are structured.
Also curious — was the...
Thanks for the thoughtful questions — really appreciate the feedback.
For this project, I worked with a single flat transactional dataset that captured booking, cancellation, pricing, and revenue fields together rather than separating them into a star schema.
On forecasting, the...
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Project Title:
Sales Performance Dashboard Using Power BI
Description Example:
Designed an interactive Power BI dashboard to track sales performance, revenue trends and monthly KPIs. Automated data transformation using Power Query and built dynamic Excel models for reporting accuracy.
Tools Used:
• Microsoft Excel
• Power Query
• Power BI
Clean layout.
Curious — did you design the data model in a star schema, or were the relationships handled directly inside Power BI?
In my experience, long-term maintainability depends more on the model layer than the visuals.
Most dashboards fail before they are even built.
Not because of bad charts.
Not because of wrong formulas.
Because the data underneath is structurally broken.
Here’s what I see often in small businesses:
• Dates stored as text
• Multiple columns for the same metric
• Inconsistent naming (Revenue / Sales / Total Sales)
• Manual copy-paste every week
• No clear data flow
Then they ask:
“Why doesn’t this dashboard update properly?”
A dashboard is just a mirror.
If the data structure is messy, the reflection will be distorted.
Before I build any report, I focus on 3 things:
Standardized column logic
Single source of truth
Repeatable data flow (no manual dependency)
Clean structure → Reliable metrics → Better decisions.
If your reporting feels fragile, the issue usually isn’t Excel.
It’s the foundation.
Completely agree. Dashboards amplify whatever foundation they sit on — messy data → misleading clarity. Standardization and single source of truth are massively underrated.
Strong hierarchy decisions here.
Invoice builders are tricky — easy to either overcrowd or oversimplify. This sits in a really good middle ground.
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