I'm a Data Analyst & Data Scientist.
Hello! I'm Nicole Kutswa, a data analyst based in Nairobi Kenya. I’m very passionate about the work that I do.
What I Do?
I turn raw data into meaningful insights that drive smart decisions. As a data analyst with a growing foundation in data science, I specialize in uncovering patterns, simplifying complexity, and presenting findings in clear, actionable ways. I use Excel for quick data exploration, SQL to extract and manipulate large datasets, and Python for in-depth analysis and automation. I also build interactive dashboards that transform complex data into clear visuals, enabling stakeholders to make confident, data-backed decisions.
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Data Mining
80 % -
Data Cleaning
100 % -
Data Analysis
100 % -
Data Visualisation
100 %
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Data Mining
I use tools like SQL and Python (Pandas, NumPy) to extract meaningful patterns from large datasets. This helps uncover trends and insights that support data-driven decisions and business strategy.
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Data Cleaning
Using Excel, Python (Pandas), and SQL, I clean and organize messy data by handling missing values, duplicates, and inconsistencies. Clean data ensures my analyses are accurate, reliable, and ready for visualization or modeling.
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Data Analysis
I apply statistical techniques and logical reasoning using Python, Excel, and SQL to uncover patterns, trends, and correlations. My goal is to turn raw data into actionable insights that solve real-world problems.
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Data Visualisation
I create interactive and insightful visuals using Excel charts, Matplotlib, Seaborn, and dashboard tools like Power BI and Tableau. These visuals help simplify complex data and communicate insights clearly to both technical and non-technical audiences.
Latest Projects
Check out some of my latest projects.
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Deep-Learning
Sales Time Series Forecasting
This project applies deep learning techniques to forecast future product sales using historical store-item data. The goal is to model and predict monthly sales for each store and item combination, capturing complex temporal patterns such as seasonality, trends, and sales volatility.
See Project
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Classification-Regression
Telecom Customer Churn Analysis
Predictive analysis project focused on identifying factors influencing customer churn in the telecom industry using Python, Pandas, and machine learning models.
See Project