Financial Data Analyst | Public Finance & Budget Management Specialist
I am a Financial Management Analyst with over two decades of extensive experience in public sector budgeting and government financial management (APBN). Throughout my career, I have managed complex budget lifecycles, ensuring fiscal accountability and transparency for multi-billion IDR funds.
Currently, I am leveraging my deep financial expertise with modern data analytics tools like SQL, Python, and Tableau. My goal is to transform intricate financial and operational data into actionable insights that drive efficiency and support data-driven decision-making in public finance and beyond.
Financial Management Analyst & Expenditure Treasurer | Regional Office of Ministry of Religious Affairs (2023 - Present)
- Managed the full budget lifecycle for three work units totaling IDR 14 billion using SAKTI (Full Web Module) and CMS, ensuring compliant digital disbursement and financial accountability while supporting more efficient budget monitoring and reporting processes.
- Automated tax administration and financial reconciliation processes using Coretax and BSrE e-signature, enabling faster verification and more accurate monthly financial accountability reports.
- Consolidated multi-unit budgets through the SAKTI system and MyInterss System, achieving fully reconciled financial statements across work units and ensuring timely submission to the State Treasury with no major discrepancies.
- Master of Economics and Business (M.Si) | University of Bengkulu (Development Planning)
- Full-Stack Data Analytics | RevoU (2025 - 2026)
- Certified Data Analyst | BNSP (2026)
- Background: Analyzed patient waittimes and satisfaction scores at RS RevoU to identify operational bottlenecks.
- Method: Performed EDA and Linear Regression using SQL and Spreadsheet; visualized patient admission trends and satisfaction heatmaps in Tableau.
- Result: Identified peak admission hours (10 AM & 10 PM) and unit-specific satisfaction gaps, providing data-backed recommendations for optimized staff shifting.
- ๐ View Repository | ๐ Tableau Dashboard
Tools: SQL | Spreadsheet | Tableau
Goal: Identify operational bottlenecks by analyzing patient waiting times and satisfaction scores.
Key Insight:
Peak admission hours occur at 10 AM and 10 PM, indicating staffing optimization opportunities.
๐ Repository | ๐ Tableau Dashboard
- Background: Investigated a 20.4% churn rate among 10,000 bank customers to identify high-risk segments.
- Method: Analyzed customer demographics (age, credit score, product usage) using SQL and built an interactive retention dashboard.
- Result: Discovered that customers aged 50-59 had the highest churn rate (56%), leading to a strategic recommendation for targeted senior-citizen loyalty programs.
- ๐ View Repository | ๐ Tableau Dashboard
- Background: Created a tracking system to monitor real-time spending habits and ensure budget compliance.
- Method: Processed 1,000+ transactions using Python (Pandas) and designed a comprehensive financial overview in Tableau.
- Result: Mapped IDR 508M in total expenses, identifying top merchants and spending categories to enable better personal fiscal discipline.
- ๐ View Repository | ๐ Tableau Dashboard
- Languages: Python (Pandas, NumPy, Matplotlib, Seaborn), SQL (BigQuery, PostgreSQL).
- Tools: Tableau, Google Looker Studio, Spreadsheet (Advanced).
- Expertise: Budgeting (APBN), Financial Reporting, Data Visualization, EDA.
- Soft Skills: Analytical Thinking, Attention to Detail, Problem Solving, Data Interpretation, Stakeholder Coordination, Communication Skills, Time Management.
- LinkedIn: linkedin.com/in/vennydeslaweny
- Instagram: https://www.instagram.com/venny_amilia/
- Email: ve.200501@gmail.com
