• Firstly, we will be using the GitHub API to gather up-to-date data from various repositories. However, before we send this data to Google BigQuery, we will thoroughly clean and transform it to ensure its accuracy and relevance. Once we have the data ready, we will carry out an exploratory data analysis within Google BigQuery to discover patterns and insights in the data.

• In the second part of the project, we will focus on designing a logical database for an eCommerce website. This database will automate the process of signing up vendors, making it more efficient and seamless.

So let's start with the GitHub repos project.

• Python 3.6 or later
• GitHub API
• Google Authentication

• Clone the repository:

git clone https://github.com/usmananwaar-de/github-repos/

• Install the required libraries by running the command

pip install -r requirements.txt

• Write GitHub API

Open the github-repos-etl.ipynb notebook and replace < Token > with your github api

• Run the code and repos data after cleaning and transformation will be available in your google bigquery account.

  Make sure your project id in google.oauth is same as in script

The logical database consists of several tables, each with a specific purpose. The vendor table contains the basic information of vendors, such as name, email, and address. The product table contains the details of the products offered by the vendors, including name, description, price, and category.

To ensure efficient inventory management, the inventory table is used to track the stock levels of each product. The payment table stores payment details, including the payment method, transaction ID, and amount paid. Finally, the shipping table tracks the delivery status of each order, including the shipping date and delivery address.

This logical database design ensures the smooth and seamless automation of the vendor sign-up process, enabling eCommerce businesses to operate more efficiently and effectively.

Thank you for reading!