Portfolio
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A selection of projects demonstrating my skills in data analysis, visualization, and automation.
1. Inventory Management & Operational Dashboard
Tools: SQL (Supabase), Vite, Excel VBA, REST APIs
Objective: To provide real-time visibility into inventory levels, sales performance, and key operational metrics for a trading company.
Action: Designed and built a custom web-based dashboard that connected directly to the company's database. Automated the extraction and transformation of daily sales and inventory data.
Result: Reduced time spent on manual inventory reporting by 6+ hours per week and helped decrease overstocking of slow-moving items by 20%.
π View Case Study (link to a detailed page with screenshots, code snippets, and deeper explanation)
2. AI-Powered Customer Support Voice Agent
Tools: Twilio, React, Supabase, Meta Llama LLM, RAG, TTS/STT, Ngrok
Objective: To automate initial customer inquiries (reservations, service questions) and provide 24/7 support.
Action: Developed a voice-enabled AI assistant using conversational AI and speech technologies. Integrated it with a central database for accurate information retrieval.
Result: Created a functional prototype capable of handling common queries, demonstrating a potential 70% reduction in routine call volume for a support team.
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3. Sales Performance & KPI Reporting Automation
Tools: Excel VBA, Office Scripts, Power BI, SQL
Objective: To eliminate manual data compilation for monthly sales reports and provide dynamic performance insights.
Action: Automated the aggregation of sales data from multiple sources and built a dynamic Power BI dashboard for visualization.
Result: Automated 8+ recurring reports, saving 6+ hours of manual work weekly and ensuring stakeholders always had access to the latest data.
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4. Tourism Client Analytics Dashboard
Tools: Google Sheets, SQL, Data Visualization
Objective: To analyze customer booking patterns and revenue data to identify growth opportunities.
Action: Built an interactive dashboard to visualize booking trends, customer demographics, and revenue streams.
Result: Provided data-backed recommendations that supported an increase in conversion rates for targeted marketing campaigns.
π View Case Study