A comprehensive Sales Performance Dashboard developed to analyze and visualize sales data, providing actionable insights for business decision-making. This project utilizes Python for data preprocessing and Looker Studio for creating interactive visualizations.
This project involves analyzing sales performance data to identify key trends, regional performance, product popularity, and segment-specific insights. The dashboard helps businesses make informed decisions to enhance sales strategies.
- Python: Data preprocessing and analysis
- Looker Studio: Data visualization and dashboard creation
- Libraries: Pandas, Matplotlib (for initial analysis in Python)
- Sales Trends Over Time: Visualizes sales fluctuations and identifies periods of high and low sales activity.
- Sales by Region: Compares sales performance across different regions to highlight regional strengths and weaknesses.
- Top Products by Sales: Displays the top-selling products to guide inventory and marketing strategies.
- Sales by Category: Breaks down sales performance by product categories to focus on high-performing categories.
- Sales by Segment: Analyzes sales performance across different customer segments to optimize marketing strategies.
- Sales by State: Provides insights into state-specific performance for targeted resource allocation and strategy development.
- Data Loading: Load the dataset using Pandas.
- Data Cleaning: Handle missing values, fix data types, and prepare the data for analysis.
- Exploratory Data Analysis (EDA): Perform initial analysis to uncover trends and patterns.