retial_sales anlaysis using sql, this project includes data cleaning, analysis, and insights on retail sales performances.
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Updated
Feb 14, 2025
retial_sales anlaysis using sql, this project includes data cleaning, analysis, and insights on retail sales performances.
Descriptive and Predictive Analysis with Interactive Dashboard
This project focuses on predicting retail sales using historical sales data and time-series regression techniques. It leverages Python, Scikit-learn, and XGBoost to build predictive models capable of forecasting sales trends. The goal is to provide actionable insights to retailers for inventory and sales strategy planning.
Conducted exploratory data analysis (EDA) using Python and Pandas to analyze performance metrics across retail regions, identifying key drivers of revenue growth and providing strategic sales recommendations through SQL insights.
This project is designed to demonstrate SQL skills and techniques typically used by data analysts to explore, clean, and analyze retail sales data. The project involves setting up a retail sales database, performing exploratory data analysis (EDA), and answering specific business questions through SQL queries.
SQL-based retail sales analysis project that includes data cleaning, exploratory queries, and business insights such as customer behavior, category performance, and sales trends across time.
Exploratory Data Analysis Projects
This project involves analyzing retail sales data using SQL to uncover insights into sales patterns, customer behavior, and product performance. It serves as an exercise to develop foundational SQL skills in data exploration, cleaning, and analysis.
Engineered PowerBI P&L financial dashboard that identified cost inefficiencies, leading to a 10% cost reduction and a 7% increase in profitability for a national retail chain.
To Develop the Retail Insights Sales API Task By Using Flask
This project is an end-to-end retail sales analytics workflow created using uncleaned real-world retail data. The main objective was to clean messy raw data, prepare it for analysis, build meaningful KPIs using SQL, and create an interactive Power BI dashboard that provides insights into customer behavior, sales performance, and product trends.
📊 Analyze retail sales data with Python and SQL, gain insights through KPIs, and visualize trends using an interactive Power BI dashboard.
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