How to load data from Google Directory to BigQuery

Learn how to use Airbyte to synchronize your Google Directory data into BigQuery within minutes.

Try Airbyte Cloud

Get a demo

Building your pipeline or Using Airbyte

Airbyte is the only open solution empowering data teams to meet all their growing custom business demands in the new AI era.

Building in-house pipelines

Bespoke pipelines are:

Inconsistent and inaccurate data
Laborious and expensive
Brittle and inflexible

Furthermore, you will need to build and maintain Y x Z pipelines with Y sources and Z destinations to cover all your needs.

After Airbyte

Airbyte connections are:

Reliable and accurate
Extensible and scalable for all your needs
Deployed and governed your way

All your pipelines in minutes, however custom they are, thanks to Airbyte’s connector marketplace and Connector Builder.

Start syncing with Airbyte in 3 easy steps within 10 minutes

Set up a Google Directory connector in Airbyte

Connect to Google Directory or one of 400+ pre-built or 10,000+ custom connectors through simple account authentication.

Set up BigQuery for your extracted Google Directory data

Select BigQuery where you want to import data from your Google Directory source to. You can also choose other cloud data warehouses, databases, data lakes, vector databases, or any other supported Airbyte destinations.

Configure the Google Directory to BigQuery in Airbyte

This includes selecting the data you want to extract - streams and columns -, the sync frequency, where in the destination you want that data to be loaded.

Try Airbyte Cloud

Take a virtual tour

Check out our interactive demo and our how-to videos to learn how you can sync data from any source to any destination.

Demo video of Airbyte Cloud

Demo video of AI Connector Builder

Talk to our team

Old Automated Content

TL;DR

set up Google Directory as a source connector (using Auth, or usually an API key)
set up BigQuery as a destination connector
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 Google Directory

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.

What is BigQuery

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.

Integrate Google Directory with BigQuery in minutes

Try for free now

Prerequisites

A Google Directory account to transfer your customer data automatically from.
A BigQuery account.
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 Google Directory and BigQuery, for seamless data migration.

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

Step 1: Set up Google Directory as a source connector

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.

Step 2: Set up BigQuery as a destination connector

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.

Step 3: Set up a connection to sync your Google Directory data to BigQuery

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

Create a new connection: On the Airbyte dashboard, navigate to the 'Connections' tab and click the '+ New Connection' button.
Choose your source: Select Google Directory from the dropdown list of your configured sources.
Select your destination: Choose BigQuery from the dropdown list of your configured destinations.
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.
Select the data to sync: Choose the specific Google Directory objects you want to import data from towards BigQuery. You can sync all data or select specific tables and fields.
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.
Test your connection: Click the 'Test Connection' button to make sure that your setup works. If the connection test is successful, save your configuration.
Start the sync: If the test passes, click 'Set Up Connection'. Airbyte will start moving data from Google Directory to BigQuery according to your settings.

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

Use Cases to transfer your Google Directory data to BigQuery

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

Advanced Analytics: BigQuery’s powerful data processing capabilities enable you to perform complex queries and data analysis on your Google Directory data, extracting insights that wouldn't be possible within Google Directory alone.
Data Consolidation: If you're using multiple other sources along with Google Directory, syncing to BigQuery 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.
Historical Data Analysis: Google Directory has limits on historical data. Syncing data to BigQuery allows for long-term data retention and analysis of historical trends over time.
Data Security and Compliance: BigQuery provides robust data security features. Syncing Google Directory data to BigQuery ensures your data is secured and allows for advanced data governance and compliance management.
Scalability: BigQuery can handle large volumes of data without affecting performance, providing an ideal solution for growing businesses with expanding Google Directory data.
Data Science and Machine Learning: By having Google Directory data in BigQuery, you can apply machine learning models to your data for predictive analytics, customer segmentation, and more.
Reporting and Visualization: While Google Directory provides reporting tools, data visualization tools like Tableau, PowerBI, Looker (Google Data Studio) can connect to BigQuery, providing more advanced business intelligence options. If you have a Google Directory table that needs to be converted to a BigQuery table, Airbyte can do that automatically.

Wrapping Up

To summarize, this tutorial has shown you how to:

Configure a Google Directory account as an Airbyte data source connector.
Configure BigQuery as a data destination connector.
Create an Airbyte data pipeline that will automatically be moving data directly from Google Directory to BigQuery after you set a schedule

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:

Easily address your data movement needs with Airbyte Cloud

Take the first step towards extensible data movement infrastructure that will give a ton of time back to your data team.

Get started with Airbyte for free

Talk to a data infrastructure expert

Get a free consultation with an Airbyte expert to significantly improve your data movement infrastructure.

Talk to sales

Improve your data infrastructure knowledge

Subscribe to our monthly newsletter and get the community’s new enlightening content along with Airbyte’s progress in their mission to solve data integration once and for all.

Subscribe to newsletter

What sets Airbyte Apart

Modern GenAI Workflows

Streamline AI workflows with Airbyte: load unstructured data into vector stores like Pinecone, Weaviate, and Milvus. Supports RAG transformations with LangChain chunking and embeddings from OpenAI, Cohere, etc., all in one operation.

Move Large Volumes, Fast

Quickly get up and running with a 5-minute setup that supports both incremental and full refreshes, for databases of any size.

An Extensible Open-Source Standard

More than 1,000 developers contribute to Airbyte’s connectors, different interfaces (UI, API, Terraform Provider, Python Library), and integrations with the rest of the stack. Airbyte’s Connector Builder lets you edit or add new connectors in minutes.

Full Control & Security

Airbyte secures your data with cloud-hosted, self-hosted or hybrid deployment options. Single Sign-On (SSO) and Role-Based Access Control (RBAC) ensure only authorized users have access with the right permissions. Airbyte acts as a HIPAA conduit and supports compliance with CCPA, GDPR, and SOC2.

Fully Featured & Integrated

Airbyte automates schema evolution for seamless data flow, and utilizes efficient Change Data Capture (CDC) for real-time updates. Select only the columns you need, and leverage our dbt integration for powerful data transformations.

Enterprise Support with SLAs

Airbyte Self-Managed Enterprise comes with dedicated support and guaranteed service level agreements (SLAs), ensuring that your data movement infrastructure remains reliable and performant, and expert assistance is available when needed.

What our users say

Jean-Mathieu Saponaro

Data & Analytics Senior Eng Manager

"The intake layer of Datadog’s self-serve analytics platform is largely built on Airbyte.Airbyte’s ease of use and extensibility allowed any team in the company to push their data into the platform - without assistance from the data team!"

Learn more

Chase Zieman

Chief Data Officer

“Airbyte helped us accelerate our progress by years, compared to our competitors. We don’t need to worry about connectors and focus on creating value for our users instead of building infrastructure. That’s priceless. The time and energy saved allows us to disrupt and grow faster.”

Learn more

Alexis Weill

Data Lead

“We chose Airbyte for its ease of use, its pricing scalability and its absence of vendor lock-in. Having a lean team makes them our top criteria. The value of being able to scale and execute at a high level by maximizing resources is immense”

Learn more

How to Sync Google Directory to BigQuery Manually

Step 1:

Step 2:

Step 3:

Step 4:

Step 5:

Step 6:

Step 7:

Step 8:

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.

What is Google Directory?

What data can you extract from Google Directory?

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.

How do I transfer data from Google Directory?

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 Google Directory to BigQuery as a source connector (using Auth, or usually an API key)
2. Choose a destination (more than 50 available destination databases, data warehouses or lakes) to sync data too and set it up as a destination connector
3. Define which data you want to transfer from Google Directory to BigQuery and how frequently
You can choose to self-host the pipeline using Airbyte Open Source or have it managed for you with Airbyte Cloud.

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.

Back to all tutorials

Warehouses and Lakes

Finance & Ops Analytics

How to load data from Google Directory to BigQuery

Learn how to use Airbyte to synchronize your Google Directory data into BigQuery within minutes.

Try Airbyte Cloud free

Deploy Airbyte Open Source

TL;DR

What is Google Directory

What is BigQuery

Prerequisites

Step 1: Setup Google Directory

Step 2: Setup BigQuery

Step 3: Setup a connection Use Cases Wrapping Up

Example H2

Example H3

Sync data between Google Directory and BigQuery

Get your data syncing in minutes

Try Airbyte free

TL;DR

set up Google Directory as a source connector (using Auth, or usually an API key)
set up BigQuery as a destination connector
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 Google Directory

What is BigQuery

Integrate Google Directory with BigQuery in minutes

Try for free now

Prerequisites

A Google Directory account to transfer your customer data automatically from.
A BigQuery account.
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.