Sales Data Engineering & Analytics Pipeline

processing and analyzing sales data. The objective of the project is to transform raw sales datasets into structured, analysis-ready data that can support business insights and decision-making.

The project begins with loading raw sales data and performing data cleaning and preprocessing to handle missing values, duplicates, and inconsistent formats. After the data is prepared, transformation steps are applied to structure the dataset and generate meaningful metrics such as total sales, product performance, and revenue trends.

Exploratory data analysis (EDA) is then performed to identify key patterns in the sales dataset. Multiple visualizations are generated to better understand sales distribution, product categories, and performance over time.

Key components of the project include:

Data cleaning and preprocessing of raw sales datasets

Feature engineering to derive new sales metrics

Exploratory data analysis (EDA) to uncover sales trends

Data visualization to understand revenue and product performance

Generating insights to support business decision-making

This project demonstrates practical skills in data engineering, data analysis, ETL workflows, and business data analytics.