📊 Sales Analyzing

📋 Overview

The Sales Analyzing project aims to forecast sales using historical data and visualize the insights using Power BI. This project leverages data analysis techniques and machine learning models to provide accurate predictions and actionable insights for business decisions.

🚀 Features

• Sales Forecasting: Predict future sales based on historical data using time series analysis.
• Data Visualization: Create interactive dashboards and reports to present sales trends, patterns, and forecasts.
• User-Friendly Interface: Utilize Power BI for an intuitive and accessible way to analyze data.

🛠️ Tools & Technologies

• Power BI: For data visualization and dashboard creation.
• Python: Data preprocessing and model building.
• SQL: Database management and data extraction.

📁 Project Structure

Sales_Analyzing/
│
├── Sales_Analyzing.pbix  # Power BI file with the dashboard
├── data/                 # Folder containing raw and processed data
├── models/               # Folder containing machine learning models
└── README.md             # Project documentation

📈 Visualizations

The following visualizations are included in the Power BI dashboard:

• Sales Trend: Monthly and yearly sales trends with comparison to targets.
• Forecast Analysis: Future sales predictions with confidence intervals.
• Top Products: Best-performing products by revenue and quantity sold.
• Regional Performance: Sales performance across different regions.

🎯 Objective

The primary objective of this project is to provide accurate sales forecasts to assist in inventory management, budgeting, and strategic planning.

📊 Data

The dataset used for this project includes historical sales data, product information, and regional sales distribution. Key features used for the analysis include:

• Date: Date of sale
• Product: Product category and SKU
• Sales: Sales revenue and quantity
• Region: Geographic region of the sale