(Not a joke) Gsheets as a Data Warehouse

Using Google Sheets as a Data Warehouse: A Step-by-Step Guide to Extracting and Storing Facebook Ads Data in Google Sheets

Introduction

Data warehousing is the process of collecting, managing, and storing data from various sources to support business decision-making. A data warehouse is a central repository of data that is used to analyze and report on data from different sources. It’s an essential tool for businesses that need to make data-driven decisions. In this blog post, we will discuss how to use Google Sheets as a data warehouse to store and manage data from different sources.

https://github.com/leonardohss0/google-sheets-as-a-data-warehouse

Setting up the environment

o use Google Sheets as a data warehouse, you need to set up a project in Google Cloud Console and enable the Google Drive API and Google Sheets API for the project. You also need to create and download the JSON key file for authentication. Here’s how to do it:

1. Go to Google Cloud Console and create a new project.
2. Enable the Google Drive API and Google Sheets API for the project.
3. Create a service account for the project and download the JSON key file.
4. Install the gspread and oauth2client libraries in your Python environment.

Creating a Project in Google Cloud Console

Activating the Google Sheets API

Activating the Google Drive API

Accessing the APIs and Service Accounts

Creating the Service Account

Accessing the Service Account

Creating an Access Key

Downloading the JSON with the credencials

Connecting to Google Sheets using Python

Once you have set up the environment, you can connect to Google Sheets using Python. Here’s how to do it:

1. Authenticate using the JSON key file and create a client object.
2. Open a worksheet and write data to it using the client object.
3. Read data from a worksheet using the client object.

Sharing the Google Sheets with the Service Account

Extracting data from Facebook Ads Marketing API using Python

To extract data from Facebook Ads, you can use the Facebook Ads API and the requests library in Python. Here’s how to do it:

1. Authenticate using your Facebook Ads credentials and create a session object.
2. Retrieve data from your campaigns using the session object.
3. Transform the data to prepare it for insertion into a Google Sheet.

Pulling data from Facebook Ads to Google Sheets

To pull data to Google Sheets, you can use the client object from the gspread library in Python. Here’s how to do it:

1. Authenticate using the JSON key file and create a client object.
2. Open a worksheet and insert data into it using the client object.
3. Schedule the script to run at regular intervals using a cron job or other scheduling tool.

Output of the project Gsheets as a Data Warehouse

Conclusion

Google Sheets is a powerful tool for managing and storing data. By using the Google Drive API and Google Sheets API, you can easily connect to Google Sheets using Python and extract data from various sources. In this blog post, we have discussed how to use Google Sheets as a data warehouse to store and manage data from Facebook Ads. With the right tools and techniques, you can turn Google Sheets into a powerful data warehouse for your business.

https://github.com/leonardohss0/google-sheets-as-a-data-warehouse