Joshua Fok

🛒 retail_project - Your Easy Retail Data Solution

🚀 Getting Started

Welcome to the retail_project! This application helps you easily manage and analyze retail data using powerful tools like Azure, Apache Atlas, and Power BI.

🌐 Overview

The retail_project is designed as an end-to-end retail data platform. It brings together multiple technologies to give you a seamless experience. You can analyze data, manage resources, and visualize your findings without needing any technical skills.

🔧 Features

• Data Management: Organize your retail data effectively.
• Integration with Azure: Utilize Azure’s robust cloud capabilities.
• Power BI Visualization: Create insightful reports and dashboards.
• Apache Atlas Support: Ensure data governance and lineage tracking.

🖥️ System Requirements

Before downloading, make sure your system meets the following requirements:

• Operating System: Windows 10 or later, macOS 10.15 or later
• RAM: At least 8 GB
• Storage: Minimum 1 GB free space
• Network: Internet connection for cloud services

📥 Download & Install

To get started, visit the Releases page to download the latest version of retail_project.

Download retail_project from Releases

1. Click the link above.
2. On the Releases page, look for the latest version.
3. Download the installation file for your operating system.
4. Once downloaded, double-click the file to begin installation.
5. Follow the prompts to complete the installation.

🛠️ How to Use

Step 1: Launch the Application

After installation, locate the retail_project icon on your desktop or in your applications folder. Double-click it to open the app.

Step 2: Connect to Azure

1. You will be prompted to sign in to your Azure account. If you don’t have an account, create one at Azure Portal.
2. Once logged in, the app will connect to your Azure resources.

Step 3: Import Data

1. Click on the “Import Data” option in the main menu.
2. Choose your data format (CSV or JSON).
3. Select your file and click “Import”. The application will process the data for analysis.

Step 4: Analyze Data

1. Navigate to the “Analyze” section.
2. Use the available tools to filter and visualize your data.
3. Create reports using Power BI directly within the application.

Step 5: Save & Share

After your analysis is complete, you can save your reports. Use the “Export” feature to share your findings with colleagues or stakeholders.

📊 Resources

Explore these topics to enhance your understanding and use of retail_project:

• Azure: Learn about Azure’s services for data storage and management.
• Apache Atlas: Discover how to manage data governance.
• Power BI: Explore Power BI capabilities for data visualization.

💬 Support

If you encounter any issues or need help, you can check the following resources:

• GitHub Issues
• Community Forums
• User Documentation

🔗 Related Technologies

• Python: The language behind our application.
• SQL: Used for querying data.
• Jupyter Notebook: Helpful for data analysis.

Feel free to explore these resources to maximize your use of the retail_project.

🤝 Contributing

We welcome contributions from all users. If you have suggestions, feature requests, or find bugs, let us know via the GitHub Issues page.

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For more information or to view the source code, please check the full repository.

Enjoy using retail_project!

Download retail_project from Releases