How to use Google Sheets as a database for your Business?

From business analysts to management consultants, Excel and Google Sheets have been the most popular tools used for data analysis. Google Sheets, in particular, offers a user-friendly interface that is universally familiar and makes it easy to store and manipulate data. While Google spreadsheets may not be as scalable as standard database management systems (DBMS), they are a great alternative for small datasets and provide simplicity, quickness, and cost-efficiency.

In this article, I will discuss how you can use Google Sheets as a database for your business and explore various methods to import, export, and manage data effectively.

Importing and Exporting Data from Google Spreadsheets

To start using Google Sheets as a database, you need to know how to import data from raw files or other formats. In this section, I will discuss four methods you can use to import, migrate, and export data from Google Sheets.

Method #1: Import Data Manually

The simplest way to import data into Google Sheets is by manually entering the data into different column fields. This method is suitable for small datasets with low frequency of changes or updates. For example, if you are an artist who sells paintings and records the transactions in a Google spreadsheet, you can manually enter the data like shown in the image below.

Using filters and sorting options, you can further analyze selective sections of the data. Additionally, you can easily export the data in your preferred format using the « File -> Download » option.

However, when your business expands and the dataset grows larger, you need to explore more efficient options like APIs or Nanonets. Keep reading to find out more!

Method #2: Use the Google Sheets API

The Google Sheets API is a popular method for automating the import and export of data. To use the API, you need to create a service account and complete authentication. Here are the steps to set it up:

1. Enable the Google Sheets API in the Google Cloud Console.
2. Create a new project and set up the OAuth consent screen.
3. Generate credentials for your project by creating a new service account and downloading the JSON key. Make sure to save the JSON key file securely.
4. Share the Google Sheet with the service account email address.
5. Install the necessary package by running ‘pip install google-api-python-client’.
6. Write a Python code to import the data from the transactions.csv file into a Google Spreadsheet.

import os
import csv
from google.oauth2 import service_account
from googleapiclient.discovery import build
from googleapiclient.errors import HttpError

# Set the path to your JSON key file
key_path = 'key.json'
# Set the ID of your Google Sheet
sheet_id = 'paintings_sales'

# Authenticate with the Google Sheets API using your JSON key file
creds = None
if os.path.exists(key_path):
    creds = service_account.Credentials.from_service_account_file(
        key_path, scopes=['https://www.googleapis.com/auth/spreadsheets'])

# Create a new Google Sheets API client
service = build('sheets', 'v4', credentials=creds)

# Open the CSV file and read the data
with open('transactions.csv', 'r') as csv_file:
    csv_data = csv.reader(csv_file)
    values = [row for row in csv_data]

# Set the range where you want to insert the data in your Google Sheet
range_name = 'Sheet1!A1:E'

# Build the request to insert the data into the Google Sheet
request_body = {
    'range': range_name,
    'majorDimension': 'ROWS',
    'values': values
}
request = service.spreadsheets().values().update(
    spreadsheetId=sheet_id,
    range=range_name,
    valueInputOption='USER_ENTERED',
    body=request_body
)

# Execute the request to insert the data into the Google Sheet
response = request.execute()

Method #3: Migrate Data from Other Databases

Google Spreadsheets also support easy migration of data from other databases. You can select and migrate a batch of data from other databases like Airtable and BigQuery as a CSV file and upload it to Google Sheets.

Method #4: Use Nanonets

If you receive digital invoices and want to import transaction data from them, Nanonets is the go-to solution. Nanonets is an AI-powered platform that uses machine learning algorithms to automatically extract relevant data and convert it into a spreadsheet format that can be easily imported into Google Sheets. Nanonets saves you time by eliminating manual data entry and streamlining your data entry process. With its high OCR accuracy and support for various document formats and sizes, Nanonets offers multiple OCRs tailored to specific business use cases, such as Invoice OCR and Receipt OCR.

Using Google Sheets as a Database for Your Website

Google Sheets can be a simple and cost-effective database for small websites. If you want to set up a database for your website, you can use Google Sheets to scrape data from the web and obtain the necessary information. Here’s how you can get started:

1. Open a new Google Sheet and select « Tools » and then « Script Editor ».
2. Write code scripts in the script editor to execute tasks like data import and manipulation.
3. Use built-in functions like IMPORTXML to extract data based on the XPath and URL of the website.
4. Utilize the ImportHTML function to scrape data from HTML tables, allowing you to choose specific rows or columns.
5. Use the REGEXTRACT function to extract data that matches specific patterns, such as the price of paintings or invoice numbers.

If you need more detailed instructions, check out this guide on how to use Google Sheets as a database for your website.

Using Google Sheets as a Database for a Django App

Django is a web framework that allows you to create web applications quickly. While Django comes with a built-in database called SQLite, it also supports other databases like MySQL, PostgreSQL, and Oracle. However, if you’re just starting out and need a simple database solution, Google Sheets can be a great option.

To connect Django to Google Sheets, you can use the Google Sheets API. Follow these steps:

1. Install the necessary packages and import the required modules.
2. Set up credentials for the Google Sheets API.
3. Define functions to read and write data to Google Sheets.
4. Create a Django app and define data attributes.
5. Link the app to the Google Sheets database.
6. Access, write, and manipulate the data as needed.

This method is easy to set up and use, making it ideal for beginners in the Django framework.

Using Google Sheets as a Database for a WordPress Website

For those using WordPress, there are plugins like SheetDB that allow you to connect your website to a Google Sheet and use it as a database. By linking and activating the plugin, you can display data in various formats, such as tables and graphs, and even filter and query the data.

However, it’s important to note that while Google Sheets can be a useful database solution for WordPress websites, it may not be suitable for complex or resource-intensive applications. Be mindful of hosting costs and consider other database options if necessary.

Using Google Sheets as an Inventory Database

Inventory management is essential for artists and small businesses that sell physical products online. Google Sheets provides a simple and effective solution for setting up an inventory management app using the AppSheet product. This tool offers built-in features specifically designed for inventory management, allowing you to track raw materials, orders in production, supplier orders, and price fluctuations. By maintaining a well-organized inventory database, you can avoid stock-outs, overstocking, and inventory shrinkage.

Conclusion

As we’ve seen, Google Sheets can be a versatile and cost-effective solution for small businesses and projects that require a database. It offers simplicity, easy data visualization, and access and control sharing options. However, it’s important to note that Google Sheets may not be suitable for complex databases or large datasets.

Remember to adapt and upgrade your database solution as your business expands and your data needs evolve. While Google Sheets can be a great starting point, consider other options if you require more advanced features or have security concerns.

If you’re interested in automating data entry from any data source, Nanonets’ OCR and workflow automation platform can be a valuable tool. With Nanonets, you can easily convert unstructured document data into a structured format, ensuring high data accuracy and streamlined data entry processes.

So why wait? Start leveraging the power of Google Sheets as a database for your business today!

➔ Read this article on Crawlan.com for more insights and tips on using Google Sheets as a database.