Sales Dashboard

Objective: This project aims to visualize sales data effectively to identify trends, analyze revenue distribution, and gain insights into product performance. Dataset Overview and Data Preprocessing: The dataset includes sales data with information about products, customers, dates, and transaction amounts. It may contain columns like Product ID, Customer ID, Date of Purchase, and Transaction Amount. Preprocessing involves handling missing values, removing duplicates, and creating calculated fields such as total sales. SQL Queries for Analysis: In Power BI, SQL-like queries can be formulated using Power Query. Sample queries include aggregating sales by product, calculating total revenue, and grouping data by periods (months, quarters). Insights and Findings: Through data visualization, trends in sales can be identified, such as seasonal spikes or slumps. The revenue distribution showcases which products are top performers and which might need strategic attention. Insights might reveal that certain products are consistently popular while others experience fluctuations in demand.