I will clean, analyse, and visualise your data with python and sql
About this Gig
Your data is lying to you - and you are making decisions based on it. I fix that.
I am Ruth Mutile - data analyst and ML practitioner with 10+ years experience. ALX Africa Data Science certified. BSc Data Science (Open University Kenya). My case studies are live on this profile: an Edward Royal Academy operations dashboard and a Football Draw Prediction ML model (Random Forest, 77% accuracy, 1,752 matches). Real work, real results.
WHAT YOU GET:
- Full data cleaning and validation
- - Exploratory data analysis with statistical summaries
- - Visualisations in Excel, Google Sheets, or Python
- - SQL queries for database extraction and aggregation
- - Python scripts for automation and repeatable pipelines
- - Google Sheets systems with advanced formulas and automation
- - Machine learning insights (classification, regression, clustering)
- - Clean annotated report ready for decision-makers
TOOLS: Python (Pandas, Scikit-learn, Seaborn) | SQL | Excel | Google Sheets | Power BI
Serving UK, UAE, and USA clients with boardroom-ready outputs.
Message me first - describe your data and goal. I will confirm scope within hours.
My Portfolio
FAQ
What types of data can you work with?
I can handle a wide range of data types including sales records, financial reports, customer databases, inventory logs, survey results, and operational data—whether from Excel, Google Sheets, CSV files, or exported software reports.
How long does it take to create a dashboard or report?
Turnaround time depends on the complexity and size of your dataset. A simple dashboard can be ready in 1–3 days, while more detailed projects may take 4–7 days. I’ll always provide a time estimate after reviewing your data.
Can you help me understand the insights if I’m not familiar with data analysis?
Absolutely! I not only deliver clean dashboards and reports but also provide clear explanations of the findings, what they mean for your business, and practical recommendations you can act on—even if you have no background in data

