TL;DR

This can be done by building a data pipeline manually, usually a Python script (you can leverage a tool as Apache Airflow for this). This process can take more than a full week of development. Or it can be done in minutes on Airbyte in three easy steps:

1. set up TMDb as a source connector (using Auth, or usually an API key)
2. set up Google Sheets as a destination connector
3. define which data you want to transfer and how frequently

You can choose to self-host the pipeline using Airbyte Open Source or have it managed for you with Airbyte Cloud.

This tutorial’s purpose is to show you how.

What is TMDb

What is Google Sheets

Prerequisites

1. A TMDb account to transfer your customer data automatically from.
2. A Google Sheets account.
3. An active Airbyte Cloud account, or you can also choose to use Airbyte Open Source locally. You can follow the instructions to set up Airbyte on your system using docker-compose.

Airbyte is an open-source data integration platform that consolidates and streamlines the process of extracting and loading data from multiple data sources to data warehouses. It offers pre-built connectors, including TMDb and Google Sheets, for seamless data migration.

When using Airbyte to move data from TMDb to Google Sheets, it extracts data from TMDb using the source connector, converts it into a format Google Sheets can ingest using the provided schema, and then loads it into Google Sheets via the destination connector. This allows businesses to leverage their TMDb data for advanced analytics and insights within Google Sheets, simplifying the ETL process and saving significant time and resources.

Step 1: Set up TMDb as a source connector

Step 2: Set up Google Sheets as a destination connector

Step 3: Set up a connection to sync your TMDb data to Google Sheets

Once you've successfully connected TMDb as a data source and Google Sheets as a destination in Airbyte, you can set up a data pipeline between them with the following steps:

1. Create a new connection: On the Airbyte dashboard, navigate to the 'Connections' tab and click the '+ New Connection' button.
2. Choose your source: Select TMDb from the dropdown list of your configured sources.
3. Select your destination: Choose Google Sheets from the dropdown list of your configured destinations.
4. Configure your sync: Define the frequency of your data syncs based on your business needs. Airbyte allows both manual and automatic scheduling for your data refreshes.
5. Select the data to sync: Choose the specific TMDb objects you want to import data from towards Google Sheets. You can sync all data or select specific tables and fields.
6. Select the sync mode for your streams: Choose between full refreshes or incremental syncs (with deduplication if you want), and this for all streams or at the stream level. Incremental is only available for streams that have a primary cursor.
7. Test your connection: Click the 'Test Connection' button to make sure that your setup works. If the connection test is successful, save your configuration.
8. Start the sync: If the test passes, click 'Set Up Connection'. Airbyte will start moving data from TMDb to Google Sheets according to your settings.

Remember, Airbyte keeps your data in sync at the frequency you determine, ensuring your Google Sheets data warehouse is always up-to-date with your TMDb data.

Use Cases to transfer your TMDb data to Google Sheets

Integrating data from TMDb to Google Sheets provides several benefits. Here are a few use cases:

1. Advanced Analytics: Google Sheets’s powerful data processing capabilities enable you to perform complex queries and data analysis on your TMDb data, extracting insights that wouldn't be possible within TMDb alone.
2. Data Consolidation: If you're using multiple other sources along with TMDb, syncing to Google Sheets allows you to centralize your data for a holistic view of your operations, and to set up a change data capture process so you never have any discrepancies in your data again.
3. Historical Data Analysis: TMDb has limits on historical data. Syncing data to Google Sheets allows for long-term data retention and analysis of historical trends over time.
4. Data Security and Compliance: Google Sheets provides robust data security features. Syncing TMDb data to Google Sheets ensures your data is secured and allows for advanced data governance and compliance management.
5. Scalability: Google Sheets can handle large volumes of data without affecting performance, providing an ideal solution for growing businesses with expanding TMDb data.
6. Data Science and Machine Learning: By having TMDb data in Google Sheets, you can apply machine learning models to your data for predictive analytics, customer segmentation, and more.
7. Reporting and Visualization: While TMDb provides reporting tools, data visualization tools like Tableau, PowerBI, Looker (Google Data Studio) can connect to Google Sheets, providing more advanced business intelligence options. If you have a TMDb table that needs to be converted to a Google Sheets table, Airbyte can do that automatically.

Wrapping Up

To summarize, this tutorial has shown you how to:

1. Configure a TMDb account as an Airbyte data source connector.
2. Configure Google Sheets as a data destination connector.
3. Create an Airbyte data pipeline that will automatically be moving data directly from TMDb to Google Sheets after you set a schedule