Data Analyst with experience in delivering business intelligence insights, developing dashboards, and building data pipelines. Proficient in SQL, Python, Tableau, and AWS, supporting strategic decision-making through data analysis and reporting.
This project analysed revenue performance across regions and product categories while identifying key operational challenges, particularly delivery delays, and uncovering opportunities for business growth. Using data visualisation, feature engineering, and trend analysis, it highlights how customer loyalty, discount activity, product categories, and fulfilment performance drive overall business performance.
The analysis explored customer registration patterns to identify high-performing acquisition channels, marketing engagement trends, and demographic subscription preferences, supporting stronger targeting strategies and improved data quality.
With rising customer acquisition costs, retaining existing subscribers has become essential for sustainable growth and profitability. This analysis aimed to identify the behavioural patterns and business factors contributing to customer churn while exploring opportunities to improve subscriber retention.
Built a serverless AWS ETL pipeline using Amazon Web Services services, including S3, Glue (PySpark), Lambda, IAM, and Docker to automate the transformation of raw sales data into analytics-ready Parquet files. Implemented data cleaning, standardisation, and quality filtering while reducing storage usage by ~70% (208KB → 63KB). The project solved the local pipeline deployment challenges through containerised Docker builds, enabling scalable and secure cloud-based data processing.
As TechHub Retail expanded within the competitive electronics market, this Tableau dashboard project analysed customer, sales, and product data to uncover growth opportunities, identify supplier risks, and support data-driven executive decision-making.