Database
Design & Query
In this project, designed and implemented a relational database for Pro App, a sharing economy platform, which facilitates customers in outsourcing tasks and projects to local tradespeople and suppliers. My task involved identifying key entities and relationships, creating an entity-relationship (ER) diagram, and developing the database schema. Also implemented SQL queries to address key business questions and extract insights that help improve platform operations and customer satisfaction.
Sales Data Analysis
This project involved comprehensive sales data analysis for Dibs, an organization looking to optimize their business decisions based on historical sales data. Using R programming language, the goal was to clean and analyze the data, identify key trends, and build predictive models to forecast future sales.
Customer segmentation
This project analyzes a dataset of 2,000 customers to segment them based on demographic and behavioral attributes such as age, gender, and income. Used Python for data processing, exploratory data analysis, and visualization.
Big data
Map reduce
Completed a big data project where I applied efficient data extraction and processing techniques. By extracting only the necessary data from a large dataset of song documents, was able to significantly reduce computation time and costs.
Bank client prediction
The goal of this analysis is to compare the performance of two machine learning models, Logistic Regression and Random Forest, in predicting whether a client will have overdue payments. By using features from client application and credit records, the analysis aims to assess which model can better predict a client's likelihood of having overdue payments, based on accuracy metrics.
