If you were analyzing this data, what would you look for first?
🎯 Which campaign is performing best?
📈 Which channel is driving the most engagement?
💰 Which campaign gives better ROI?
👥 Which audience is responding the most?
Built with Elldy.
I’ve been thinking about the way we approach data analytics.
Tools like Power BI make it possible to quickly build interactive reports and dashboards from your data. And that’s great when you already know what you want to measure and communicate.
But sometimes, especially when working with a new dataset, the bigger challenge is different:
What is actually interesting in this data?
Before deciding which visuals belong in a dashboard, I prefer to explore the data first:
• What are the distributions?
• Are there unusual values or outliers?
• Are two variables related?
• Are there interesting correlations?
• What patterns appear across different groups?
• Are there trends I didn’t expect?
For example, a scatter plot or box plot might reveal something you didn’t know was there. Once you discover that pattern, you can decide whether it deserves a place in the final dashboard.
This is the idea behind the Analysis Workspace in Elldy.
The workflow I’m exploring is:
Data → Explore → Find patterns → Understand → Select insights → Dashboard
Rather than starting with:
“Which dashboard should I build?”
Start with:
“What is my data telling me?”
I don’t see this as Power BI vs. Elldy. Both can be useful for different purposes.
I’m more interested in the analysis-first approach.
How do you normally work with a new dataset — explore first, or start building the dashboard?
#DataAnalytics #DataAnalysis #DataVisualization #EDA