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Sync with Airbyte
1. Go to the Google Cloud Console and create a new project.
2. Enable the Google Directory API for the project.
3. Create a new service account and download the JSON key file.
4. Grant the service account access to the Google Directory API.
5. Open Airbyte and navigate to the Sources page.
6. Click on "New Source" and select "Google Directory" from the list of available connectors.
7. Enter a name for the source and click "Next".
8. Upload the JSON key file downloaded earlier and enter the email address associated with the service account.
9. Enter the domain name for the Google Workspace account you want to connect to.
10. Click "Test Connection" to ensure the credentials are valid and the connection is successful.
11. Select the tables you want to replicate and configure any additional settings.
12. Click "Create Source" to save the configuration and start the replication process.
1. First, navigate to the Airbyte dashboard and select the "Destinations" tab on the left-hand side of the screen.
2. Scroll down until you find the "BigQuery" destination connector and click on it.
3. Click the "Create Destination" button to begin setting up your BigQuery destination.
4. Enter your Google Cloud Platform project ID and service account credentials in the appropriate fields.
5. Next, select the dataset you want to use for your destination and enter the table prefix you want to use.
6. Choose the schema mapping for your data, which will determine how your data is organized in BigQuery.
7. Finally, review your settings and click the "Create Destination" button to complete the setup process.
8. Once your destination is created, you can begin configuring your source connectors to start syncing data to BigQuery.
9. To do this, navigate to the "Sources" tab on the left-hand side of the screen and select the source connector you want to use.
10. Follow the prompts to enter your source credentials and configure your sync settings.
11. When you reach the "Destination" step, select your BigQuery destination from the dropdown menu and choose the dataset and table prefix you want to use.
12. Review your settings and click the "Create Connection" button to start syncing data from your source to your BigQuery destination.
FAQs
What is ETL?
ETL, an acronym for Extract, Transform, Load, is a vital data integration process. It involves extracting data from diverse sources, transforming it into a usable format, and loading it into a database, data warehouse or data lake. This process enables meaningful data analysis, enhancing business intelligence.
Google (Workspace) Directory is, simply put, a user management system for Google Workspace. It allows IT admins to manage users’ access, facilitates and governs user sign-ons, and, ultimately, is meant to enable users to sign in to multiple Google services through one Google identity. Other features include the ability to monitor devices connected to a business’s domain, manage organizations’ structures, audit applications to which users have approved access, and revoke unauthorized apps.
Google Directory's API provides access to a wide range of data related to the Google Directory service. The API allows developers to retrieve information about various categories of data, including:
- Directory listings: Information about businesses, organizations, and other entities listed in the Google Directory.
- Categories: The different categories and subcategories used to organize listings in the directory.
- Reviews and ratings: User-generated reviews and ratings for businesses and other entities listed in the directory.
- Contact information: Phone numbers, addresses, and other contact information for businesses and organizations listed in the directory.
- Images and videos: Images and videos associated with listings in the directory.
- User profiles: Information about users who have contributed reviews and ratings to the directory.
Overall, the Google Directory API provides developers with a wealth of data that can be used to build applications and services that leverage the information contained in the directory.
What is ELT?
ELT, standing for Extract, Load, Transform, is a modern take on the traditional ETL data integration process. In ELT, data is first extracted from various sources, loaded directly into a data warehouse, and then transformed. This approach enhances data processing speed, analytical flexibility and autonomy.
Difference between ETL and ELT?
ETL and ELT are critical data integration strategies with key differences. ETL (Extract, Transform, Load) transforms data before loading, ideal for structured data. In contrast, ELT (Extract, Load, Transform) loads data before transformation, perfect for processing large, diverse data sets in modern data warehouses. ELT is becoming the new standard as it offers a lot more flexibility and autonomy to data analysts.
Google (Workspace) Directory is, simply put, a user management system for Google Workspace. It allows IT admins to manage users’ access, facilitates and governs user sign-ons, and, ultimately, is meant to enable users to sign in to multiple Google services through one Google identity. Other features include the ability to monitor devices connected to a business’s domain, manage organizations’ structures, audit applications to which users have approved access, and revoke unauthorized apps.
BigQuery is an enterprise data warehouse that draws on the processing power of Google Cloud Storage to enable fast processing of SQL queries through massive datasets. BigQuery helps businesses select the most appropriate software provider to assemble their data, based on the platforms the business uses. Once a business’ data is acculumated, it is moved into BigQuery. The company controls access to the data, but BigQuery stores and processes it for greater speed and convenience.
1. Go to the Google Cloud Console and create a new project.
2. Enable the Google Directory API for the project.
3. Create a new service account and download the JSON key file.
4. Grant the service account access to the Google Directory API.
5. Open Airbyte and navigate to the Sources page.
6. Click on "New Source" and select "Google Directory" from the list of available connectors.
7. Enter a name for the source and click "Next".
8. Upload the JSON key file downloaded earlier and enter the email address associated with the service account.
9. Enter the domain name for the Google Workspace account you want to connect to.
10. Click "Test Connection" to ensure the credentials are valid and the connection is successful.
11. Select the tables you want to replicate and configure any additional settings.
12. Click "Create Source" to save the configuration and start the replication process.
1. First, navigate to the Airbyte dashboard and select the "Destinations" tab on the left-hand side of the screen.
2. Scroll down until you find the "BigQuery" destination connector and click on it.
3. Click the "Create Destination" button to begin setting up your BigQuery destination.
4. Enter your Google Cloud Platform project ID and service account credentials in the appropriate fields.
5. Next, select the dataset you want to use for your destination and enter the table prefix you want to use.
6. Choose the schema mapping for your data, which will determine how your data is organized in BigQuery.
7. Finally, review your settings and click the "Create Destination" button to complete the setup process.
8. Once your destination is created, you can begin configuring your source connectors to start syncing data to BigQuery.
9. To do this, navigate to the "Sources" tab on the left-hand side of the screen and select the source connector you want to use.
10. Follow the prompts to enter your source credentials and configure your sync settings.
11. When you reach the "Destination" step, select your BigQuery destination from the dropdown menu and choose the dataset and table prefix you want to use.
12. Review your settings and click the "Create Connection" button to start syncing data from your source to your BigQuery destination.
With Airbyte, creating data pipelines take minutes, and the data integration possibilities are endless. Airbyte supports the largest catalog of API tools, databases, and files, among other sources. Airbyte's connectors are open-source, so you can add any custom objects to the connector, or even build a new connector from scratch without any local dev environment or any data engineer within 10 minutes with the no-code connector builder.
We look forward to seeing you make use of it! We invite you to join the conversation on our community Slack Channel, or sign up for our newsletter. You should also check out other Airbyte tutorials, and Airbyte’s content hub!
What should you do next?
Hope you enjoyed the reading. Here are the 3 ways we can help you in your data journey:
What should you do next?
Hope you enjoyed the reading. Here are the 3 ways we can help you in your data journey:
Ready to get started?
Frequently Asked Questions
Google Directory's API provides access to a wide range of data related to the Google Directory service. The API allows developers to retrieve information about various categories of data, including:
- Directory listings: Information about businesses, organizations, and other entities listed in the Google Directory.
- Categories: The different categories and subcategories used to organize listings in the directory.
- Reviews and ratings: User-generated reviews and ratings for businesses and other entities listed in the directory.
- Contact information: Phone numbers, addresses, and other contact information for businesses and organizations listed in the directory.
- Images and videos: Images and videos associated with listings in the directory.
- User profiles: Information about users who have contributed reviews and ratings to the directory.
Overall, the Google Directory API provides developers with a wealth of data that can be used to build applications and services that leverage the information contained in the directory.
What should you do next?
Hope you enjoyed the reading. Here are the 3 ways we can help you in your data journey: