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An R-based statistical analysis project studying water table depth and fluctuation patterns across the Rift Valley region. Uses hydrological survey data to model seasonal trends, identify areas at risk of water stress, and generate visualizations that researchers and county water departments can use for resource planning. Core outputs are regression models and publication-ready plots.
The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
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Apotelesma is a professional workspace for chart analysis, built entirely solo — from a real astronomical calculation engine to a fully custom, interactive UI. It connects multiple analytical techniques into one continuous workflow instead of treating them as separate, disconnected tools, with live data panels, saved states, and a system for organizing findings per client. Architected, designed, and shipped end to end. Live at apotelesma.org.
Impressive work! Building the calculation engine, interactive UI, and end-to-end workflow as a solo project is a significant achievement. I especially like the focus on bringing multiple analytical techniques together into one cohesive workspace instead of treating them as isolated tools
Your Supabase app is working… but your database is still exposed? 🔐
One mistake I see developers make is setting up authentication and forgetting about Row Level Security (RLS).
If you're using Supabase, don't just create your tables and move on.
Make sure you:
✅ Enable RLS on your tables
✅ Create policies for who can read data
✅ Create policies for who can insert or update data
✅ Never expose sensitive service keys in the frontend
✅ Test your policies with different user accounts
Authentication tells you who the user is. RLS helps control what they can access.
Have you ever had an RLS policy block something that should have worked? 👇
Impressive, thanks for the tips love ❤️
E-Commerce Super Store Sales Dashboard
Developed an interactive Power BI dashboard to analyze sales performance, profitability, customer trends, and operational KPIs for an e-commerce business. The dashboard provides decision-makers with real-time insights into sales growth, product performance, returns, and regional trends through dynamic and visually engaging reports.
Key Highlights
Designed an executive-style dashboard with an intuitive user experience
Built dynamic KPIs using DAX for Sales, Quantity, Returns, and Delivery Performance
Cleaned and transformed data using Power Query
Created an optimized data model for accurate and efficient reporting
Implemented interactive filters, cross-filtering, and time-based analysis
Visualized sales by country, product, category, customer, market, and monthly trends.
Skills Used
Power BI • DAX • Power Query • Data Modeling • ETL • Sales Analytics • KPI Development • Data Visualization • Business Intelligence
