https://github.com/sohanoor/seleniumpythonjs

This project outlines a comprehensive approach to automating sales data management and order processes, leveraging advanced tools and techniques for optimal business performance.
https://github.com/sohanoor/seleniumpythonjs

business-analytics python sales selenium-python selenium-webdriver

Last synced: 15 days ago
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This project outlines a comprehensive approach to automating sales data management and order processes, leveraging advanced tools and techniques for optimal business performance.

• Host: GitHub
• URL: https://github.com/sohanoor/seleniumpythonjs
• Owner: sohanoor
• Created: 2024-05-11T05:06:02.000Z (8 months ago)
• Default Branch: main
• Last Pushed: 2024-09-12T14:40:27.000Z (4 months ago)
• Last Synced: 2024-11-09T19:12:04.368Z (2 months ago)
• Topics: business-analytics, python, sales, selenium-python, selenium-webdriver
• Language: Python
• Homepage:
• Size: 8.6 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
Documentation

#### Aim

The aim of this project is to develop an automated solution for collecting and analyzing sales data, comparing vendor offers, and managing product orders efficiently. By leveraging Microsoft Excel, Python, Selenium, and Power BI, the project will streamline the process of data collection, price comparison, inventory management, and order placement, ultimately enhancing decision-making and operational efficiency.

#### Motivation

In today's competitive market, businesses need to optimize their procurement processes to remain cost-effective and responsive to market changes. Manual processes for data collection, price comparison, and order management are time-consuming and prone to errors. Automating these processes will not only save time but also improve accuracy, leading to better financial decisions and operational efficiency.

#### Steps

1. **Collect Sales Data in Excel:**

   - Gather historical sales data and store it in Microsoft Excel for analysis.

2. **Login to Vendor Website with Authentication:**

   - Use Selenium to automate the login process to the vendor’s website, including handling authentication mechanisms.

3. **Collect Vendor Offers:**

   - Scrape the latest offers from the vendor’s website using Selenium and store the data in Excel.

4. **Collect Product List with Prices:**

   - Extract product details and prices from the vendor's website and save this information in Excel.

5. **Compare Lowest Prices:**

   - Use Python to compare vendor prices with existing product prices and identify the lowest prices.

6. **Compare Product Data from Sales and Stock Report:**

   - Analyze and compare product data from sales reports and stock reports using Python.

7. **Predict Product Quantity for Next Week:**

   - Apply predictive analytics techniques in Python to forecast the required product quantity for the upcoming week.

8. **Create Product List for Next Order:**

   - Based on the predictions and current inventory, generate a list of products required for the next order.

9. **Place the Order:**

   - Automate the order placement process using Python and Selenium to interact with the vendor’s ordering system.

10. **Visualize Data with Power BI:**

    - Import the collected data into Power BI to create interactive dashboards and reports for insightful visualization and decision-making.

#### Technical Details

- **Microsoft Excel:** Used for data storage, organization, and preliminary analysis.

- **Python:** Utilized for data processing, analysis, and predictive modeling. Key libraries include pandas, NumPy, and scikit-learn.

- **Selenium:** Employed for web automation tasks such as logging into vendor websites, scraping data, and placing orders.

- **Power BI:** Used to create interactive visualizations and dashboards for data analysis and reporting.

#### Business Benefits

- **Increased Efficiency:** Automation of data collection and order placement reduces manual effort and operational time.

- **Enhanced Accuracy:** Minimizes errors associated with manual data entry and calculations.

- **Cost Savings:** By comparing prices and optimizing order quantities, the business can reduce procurement costs.

- **Informed Decision-Making:** Data visualization and predictive analytics enable better forecasting and strategic planning.

#### Knowledge Acquired

- **Web Automation:** Skills in using Selenium for automating web interactions and data extraction.

- **Data Analysis:** Experience with Python libraries for data processing, comparison, and predictive analytics.

- **Data Visualization:** Proficiency in Power BI for creating and interpreting interactive dashboards and reports.

- **Integration:** Understanding of integrating various tools (Excel, Python, Selenium, Power BI) to achieve comprehensive automation and analysis.

#### Future Plan

- **Expand Vendor Integration:** Incorporate additional vendor websites and platforms to broaden the scope of price comparison and order management.

- **Enhance Predictive Models:** Refine predictive analytics techniques to improve accuracy in forecasting product quantities.

- **Automate Reporting:** Develop automated reporting features to generate regular updates and insights.

- **User Interface Development:** Create a user-friendly interface for easier interaction with the automated system and data visualization tools. 

This project documentation outlines a comprehensive approach to automating sales data management and order processes, leveraging advanced tools and techniques for optimal business performance.