You will get a clean, analysis-ready datasets from your messy Excel or CSV files
Project details
Good analysis starts with clean data. I’ve worked on 100+ published projects across retail, F&B, banking, property, and ecommerce, all starting from messy raw files.
You’ll receive a clean dataset in 1–3 days, plus a clear summary of every fix made. Just send the file and a short note about the data, and I’ll handle the rest.
You’ll receive a clean dataset in 1–3 days, plus a clear summary of every fix made. Just send the file and a short note about the data, and I’ll handle the rest.
Data Tool
PythonWhat's included
| Service Tiers |
Starter
$100
|
Standard
$150
|
Advanced
$200
|
|---|---|---|---|
| Delivery Time | 1 day | 2 days | 3 days |
Number of Revisions | 1 | 2 | 3 |
Frequently asked questions
About Lee
Data Analyst - Dashboards, Power BI and Reports
Banting, Malaysia - 10:03 pm local time
I work with SME owners and teams across retail, F&B, property, banking, and education, on forecasting, churn, customer value, pricing, segmentation, and hypothesis testing. Every engagement is a complete, usable output, not just analysis: typically a cleaned dataset, a analyst report, an interactive dashboard with real filters, and, where it helps, an optional AI assistant that answers questions directly from your own data.
What I can help you with
• Interactive dashboards and Power BI reports (filterable, decision-focused, not static)
• Excel and Google Sheets dashboards, KPI workbooks, and data cleanup
• Cohort and retention analysis, churn modeling, RFM and customer segmentation
• Pricing and margin analysis, demand forecasting, peak and seasonality planning
• Hypothesis testing with clear interpretation (not just statistics)
• Optional: an AI assistant that works on top of your data (MCP-based)
Selected work
• Multi-page Power BI store-revenue dashboard: what drives revenue, by product, channel, and region.
• Loan Approval Risk and Fairness Dashboard: an interactive tool to check risk and fairness in seconds.
• High-Value Customer Segmentation: which customers to target, retain, and grow (RFM and CLV).
• KPI Composite Workbook (Excel and Power Query): a refreshable peer-benchmark with an auto-written summary.
• Bank Customer Churn Model: which customers are likely to leave, and why.
• AI Assistants (optional add-on): ask questions in plain language and get answers from your real data.
How I work
• Fast turnaround for clearly scoped projects (typically 3 to 5 days)
• Clear, non-technical explanations, built for business decisions, not analysts
• Structured outputs you can reuse, not one-off reports
Stack
Power BI, Excel and Power Query, Looker Studio, SQL, Python (Pandas, scikit-learn), Chart.js
Optional data-grounded AI assistants: Gemini, Claude, MCP, FastAPI, Cloud Run
Steps for completing your project
After purchasing the project, send requirements so Lee can start the project.
Delivery time starts when Lee receives requirements from you.
Lee works on your project following the steps below.
Revisions may occur after the delivery date.
Review
I receive your file and review what each column represents.
Audit
I check for duplicates, missing values, inconsistent dates, unusual labels, and outliers.