Infer SQL DDL statements from tabular data.

🔷 Customer Segmentation Using RFM Analysis 🔷 This project applies RFM (Recency, Frequency, Monetary) analysis to segment customers based on their purchasing behavior. Using Python (Pandas, Seaborn, Matplotlib), we calculated RFM scores and grouped customers into segments like Champions, Loyal, At Risk, and Hibernating.

A series of R scripts to clean and preprocces Football-Data.co.uk data.

JavaScript binding for the Rowslint CSV importer

static data importer CLI - import csv, json or xml as entity objects

Exploratory data analysis with SAS on Insurance datatsets. Performed Data Importing, Data Managing, Merging and Basic Statistics operations.

Sentiment analysis of The INKEY List skincare reviews from the Sephora dataset using BERT, zero-shot classification, and TF-IDF with logistic regression. This project classifies reviews into positive, negative, or neutral sentiments, offering insights into customer satisfaction.

Objective: To develop a comprehensive credit card weekly dashboard that provides real time insights into key performance indicators and trends enabling stakeholders to monitor and analyse credit card operations effectively

Angular binding for the Rowslint CSV importer

This repository offers comprehensive projects on business analytics using Python, including big data analysis, data cleaning, importing/exporting, integration, quality assurance, time series analysis, EDA with Tableau, forecasting, regression, and sentiment analysis. Ideal for both beginners and experts.

📊 Analyze customer behavior with RFM segmentation to drive targeted marketing strategies and boost retention in retail and e-commerce.