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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.
Exactly. A dashboard doesn’t fix structural problems — it just makes them look prettier.
Most reporting errors I see come from inconsistent definitions and duplicated sources rather than formulas.
Once the structure is solid, the dashboard almost builds itself.
True. It’s interesting how teams often try to “fix clarity” at the dashboard layer instead of resolving structural inconsistencies. Have you noticed any common patterns behind those duplicated sources?
Yes — the most common pattern I see is parallel reporting. Different teams export and transform the same raw data in their own way, which creates multiple “versions of truth.”
It usually starts as a speed solution and slowly becomes a structural problem.
Centralizing the data model early prevents most of that downstream noise.
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Turning unstructured data into clean, column-based tables is such an underrated skill. Most reporting issues start from messy raw input. Do you usually automate this with Power Query or handle it manually?
Datara B2B SaaS Dashboard
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Strong visual system. Dark dashboards often lose clarity, but this stays very structured and readable — hierarchy and spacing feel well controlled.
I redesigned the admin dashboard to improve clarity, structure, and decision visibility.
The original version worked functionally, but it had a few friction points:
→ Heavy color blocks competing for attention
→ Metrics without context
→ Weak hierarchy
→ Large empty table space
→ Data displayed, but not interpreted
It showed numbers.
It didn’t guide decisions.
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1. Reduced visual noise
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3. Added contextual insights
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Really thoughtful breakdown of the friction points — especially “metrics without context” and hierarchy.
That’s where many dashboards struggle.
The redesign feels much more decision-oriented rather than data-heavy 👌
Curious if you introduced any progressive disclosure or priority states for key metrics?
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