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Most finance dashboards show you numbers. Duoflow shows you control.
Salary hits. Rent goes out. Freelance payment clears. Subscriptions quietly drain. Most people have no single view that connects all of it just anxiety and a rough mental estimate of what's left.
So I designed Duoflow to change that feeling completely.
A dark canvas with a yellow-green accent system that makes financial data feel energetic, not exhausting. Every number has context. Every category has a visual weight. Nothing is buried.
The waveform spending bar is the centerpiece. Rent, Groceries, Debt Repayment, Subscriptions, and Savings are visualized as volume, not just percentages. The three-metric header puts Total Revenue, Total Savings, and Monthly Expense in one row so the full picture lands in one glance. The income sources panel breaks down salary, freelance, and investment side by side with a dot-matrix trend chart showing exactly how June compared to July.
The goal was simple:
Open the dashboard and feel in control within five seconds.
Because financial clarity shouldn't require a finance degree. It should just require one good screen.
Designed by Orbix Studio.
#FinanceDashboard #DarkModeUI #BudgetTracker #PersonalFinance #DataVisualization #ProductDesign #UIDesign #OrbixStudio
Awesome work!
This Superstore Sales Dashboard gives an overview of sales performance across time, regions, customers, and products. Total sales are 1bn, with peak performance in Q4, showing strong seasonal trends. California and Texas are the top-performing states, while New York and Houston lead at the city level. Binders and Phones are the best-selling sub-categories. The dashboard also highlights key customers contributing to revenue and includes filters for deeper analysis. Overall, it helps in identifying trends and making data-driven decisions.
The Q4 peak and seasonal trend identification is one of the most valuable things a sales dashboard can show — once you know when your strongest period is, you can plan inventory and marketing spend around it instead of reacting after the fact.
The top customer contribution view...
Global Internet Shutdown Analysis
What the project was about:
I analyzed global internet shutdown data to understand where, when, and why shutdowns happen. The goal was to uncover patterns across countries and time periods and highlight their impact on digital access.
What I did:
Collected and cleaned real-world dataset
Performed EDA (Exploratory Data Analysis)
Analyzed shutdowns by:
Country
Year/month
Reasons (political, security, protests, etc.)
Built Power BI dashboards to visualize trends
Identified high-risk regions and frequent shutdown patterns
Key Findings:
Certain countries showed repeated shutdown patterns over time
Most shutdowns were linked to:
Political instability
Government control during protests/elections
Some regions experienced long-duration shutdowns, affecting communication and businesses
There was a rise in shutdown frequency during specific global events
Challenges I faced:
Data cleaning issues
Missing values, inconsistent country names
Unstructured reasons
Different formats for shutdown causes → needed standardization
Time-based analysis
Converting dates and extracting meaningful trends
Visualization complexity
Making dashboards simple yet insightful
How I solved them:
Cleaned and standardized data using Python (Pandas)
Grouped and categorized shutdown reasons
Used time-series analysis for trends
Designed clear and interactive Power BI dashboards
Impact / Outcome:
Provided a clear view of global digital disruptions
Helped identify high-risk regions and key causes
Created dashboards that make complex data easy to understand
This is a very insightful analysis on a highly relevant topic. I like how you handled data challenges like inconsistencies and unstructured inputs and still managed to build clear Power BI dashboards. The findings around political and regional shutdown patterns are particularly interesting.
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