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Create an advanced data engineering pipeline that processes and analyzes sales data from an e-commerce website using Apache Airflow for workflow management and ClickHouse as the high-performance data warehouse.
In this project we dive into the intriguing world of Ecommerce sales data from the year 2019. Through data wrangling, visualization, and insightful analysis, we aim to uncover trends, customer behaviors, and key factors that drove sales during that period.
ETL pipeline and data warehouse for e-commerce analytics using PostgreSQL and Python. Includes transformation scripts, schema modeling, and business insights via SQL.
E-Commerce Sales Dashboard - Excel This project involves creating an Excel dashboard to analyze e-commerce sales data. The dashboard allows users to select a product category and view sales trends by month and product. The analysis includes creating a histogram for shipping days, preparing sales and profit tables, and generating charts.
E-commerce Sales Analysis Dashboard - MS Excel This Excel dashboard is designed for analyzing e-commerce sales data. It allows you to track key metrics like sales, profit, and order quantities, while also offering insights into category performance and top-selling products. With dynamic filters and visual tools, you can easily explore trends and
Power BI Dashboard Portfolio featuring projects on sales analysis, customer insights, and business performance reporting. Includes visualizations, datasets, and interactive reports.
This project dives deep into the sales, delivery, and customer feedback data of major grocery delivery platforms – Blinkit, Swiggy Instamart, and JioMart. It is designed to showcase my ability to clean, analyze, and visualize data using Microsoft Excel.