Completed over 200 hours of hands-on training in Power BI, SQL, Python, and R, focused on applied analytics and report automation. Designed and published more than five professional dashboards covering sales, cash flow, performance metrics, and financial analysis using both simulated and real data. Advised three small businesses on organizing their commercial data, helping two of them implement monthly reporting and improve KPI tracking. Built a professional data analytics portfolio that showcases my technical growth and ability to generate actionable insights. Increased my Power BI development speed by 60%, optimizing data loading, modeling, and visualization processes. Used tools like Power BI and SQL, along with basic Python functions, to automate simple tasks and explore data more efficiently.

I worked directly with the CEO of an energy company. My role combined executive support with strategic data analysis. Built automated Power BI dashboards to monitor oil prices, clean energy trends, and financial KPIs, cutting manual updates by 80%. Structured and organized databases with key metrics, improving operational efficiency by 30%. Delivered financial and energy intelligence reports to support executive decisions and tax planning. Applied SQL queries to improve data extraction and integration in reports. Managed travel and expense data visualization for fiscal compliance and transparency.

Automated grade reporting with Excel and DAX, reducing evaluation time by 50%. Created Power BI visuals to support school leadership in performance tracking. Streamlined administrative workflows, increasing planning time by 40%. Combined teaching with data initiatives to improve traceability and communication.

I was responsible for maintaining an efficient balance between accounts payable and receivable while ensuring liquidity and supporting supplier negotiations. Automated financial reports with Excel and Power Pivot, reducing consolidation time by 60%. Designed cash flow and collections dashboards, recovering 15% of overdue accounts. Standardized reporting processes, reducing reconciliation errors by 40%. Improved liquidity forecasting by aligning payables and receivables to support operations.