Today, companies are embracing more and more digital tools to run their businesses, and as a result, they're producing a ton of valuable data. This data plays a vital role in making smart business decisions and shaping future strategies. It's becoming increasingly crucial to capture real-time event data from SaaS applications, especially the ones that provide users with important and critical access to information.

By capturing and analyzing this event data, you can establish a secure environment that safeguards sensitive data, promotes smooth operations, and ensures overall safety.

Many businesses today use big data tools such as Google BigQuery to tap into the full potential of their data. In this quickstart, we will explore how to send event data from Auth0 to Google BigQuery, so let's start by understanding what these tools are and how they work together.

Understanding Auth0 and Google BigQuery

What is Auth0?

Auth0 is a powerful identity platform that simplifies the integration of secure authentication, authorization, and user management into your applications. With Auth0, you can leverage industry-standard protocols like OAuth 2.0, benefit from Single Sign-On (SSO) capabilities, and utilize fine-grained control through scopes.

OAuth 2.0 is a widely adopted protocol for secure authorization. With Auth0, you can easily implement OAuth 2.0 in your applications, allowing users to grant limited access to their protected resources without sharing their credentials. Auth0 acts as an Authorization Server, managing the OAuth 2.0 flows, issuing access tokens, and ensuring secure communication between applications.

Auth0 provides comprehensive support for OAuth 2.0, enabling you to integrate OAuth 2.0 into your applications easily.

Auth0 also offers a range of developer tools and APIs that enable businesses to customize the authentication experience for their users. These tools include customizable login pages, password reset flows, and user management APIs.

What is Google BigQuery?

Google BigQuery is a serverless, highly scalable enterprise data warehouse designed to handle significant amounts of data. It enables businesses to store, analyze, and retrieve large datasets quickly and efficiently using SQL queries. BigQuery automatically manages the infrastructure and distributes complex analytical workloads across its serverless nodes, providing a fast and reliable processing environment.

BigQuery is designed to handle a wide range of data types, including structured, semi-structured, and unstructured data. It also offers a range of advanced features, such as machine learning, geospatial analysis, and real-time streaming ingestion.

One of the key benefits of BigQuery is its scalability. Businesses can start with a small dataset and easily scale up as their data needs grow. BigQuery also offers a pay-as-you-go pricing model, which means businesses only pay for the data they store and process.

BigQuery is fully integrated with other Google Cloud Platform services, such as Cloud Storage and Cloud Dataflow, making it easy for businesses to build end-to-end data pipelines. It also offers a range of connectors to popular third-party tools, such as Tableau and Looker.

Setting up your Auth0 account

Auth0 is an authentication and authorization platform that allows developers to add secure login and access management to their applications with ease. In the next part of this guide, we will walk you through the process of setting up your Auth0 account and configuring your application to use its features.

Creating an Auth0 application

The first step in using Auth0 is to create an account and an application for your project. To create an account, simply go to the Auth0 website and sign up for a free account.

Once you have created your account, you can create an application by navigating to the applications tab and clicking the "Create Application" button. This will take you to a page where you can provide a name for your application and select the type of application you are building.

Auth0 supports a wide range of applications including web, mobile, and single-page applications. Once you have selected the appropriate application type, you can configure your application's settings. This includes specifying the authentication method, such as username/password or social login, and any other relevant settings.

Configuring Auth0 actions

Auth0 also supports actions, which are snippets of JavaScript code that run when a user authenticates to your application. Actions can execute at certain points within the Auth0 platform and are used to customize and extend Auth0's capabilities with custom logic.

Actions can be used to create customized flows of activities that trigger off events that occur either before or after a signup activity, login, or password change.

For example, you can use rules to send user login data to CRMs like Salesforce or external data stores such as Google BigQuery, Amazon Redshift, or Snowflake. This can be useful if you want to analyze user behavior or track user activity across different applications.

Actions can also be used to implement custom password policies, such as requiring users to use strong passwords or enforcing password expiration dates. This can help to improve the security of your application and protect against password-related attacks.

Setting up your Google BigQuery account

Before we start ingesting login event data through Auth0 into BigQuery, we’ll need to set up our BigQuery account. This allows users to analyze massive datasets quickly and efficiently. Here we’ll walk you through the process of setting up your Google BigQuery account.

Creating a Google Cloud project

The first step to using Google BigQuery is to create a Google Cloud Project. This project will serve as the foundation for all of your BigQuery activities. To create a project, log in to the Google Cloud Console and click on the "Select a Project" dropdown menu. From there, choose "New Project."

Enabling the BigQuery API

After creating a project, you need to enable the BigQuery API. This is a simple process that can be completed from the Cloud Library. In the Google Cloud Console on the left side menu, click APIs & Services. Select Dashboard from the list. Simply search for "BigQuery" and enable the API for the project you've just created. It's important to note that you may need to configure billing settings if you plan on deploying significant data processing projects on this platform.

Setting up a BigQuery dataset and table

To work with BigQuery, you need to create both a dataset and a table. A dataset is a collection of tables, while a table contains the data you want to analyze. Creating a dataset and table is simple. From the BigQuery console, click on the "CREATE DATASET/TABLE" button and follow the prompts.

When creating a table, you'll need to specify the schema that describes the structure of your data. This includes the names and types of each column in your data. Once you've created your table, you can start loading your Authentication data through Auth0.

It's important to note that BigQuery supports a wide range of data formats, including CSV, JSON, and Avro. You can also load data from Google Cloud Storage or stream data into your table in real time.

Now that you've set up your BigQuery account, you're ready to start exploring your data. With its powerful querying capabilities and lightning-fast performance, BigQuery is the perfect tool for analyzing large datasets and gaining valuable insights into your business.

Note: This is one way of setting up a BigQuery account, but you can also set it up programmatically by using the bq command line interface (CLI).

Generating Google Cloud service account credentials

Before you can utilize a service account to move data from Auth0 to BigQuery, you need to generate the necessary credentials. To do this, go to the Cloud Console and navigate to IAM & admin>Service accounts. Select the project you're using with BigQuery and create a new service account. This service account will act as the intermediary between Auth0 and BigQuery and will be used to provide the app with the required permissions.

From the service account, you should select and download the JSON file containing your service account credentials. This file will be used to authenticate your requests to the BigQuery API.

As part of the service account creation process, you'll generate a private key. This key is used to sign the JSON Web Token (JWT) and verify its authenticity when it is presented to GCP services. We can use the Private key in the JSON key file we downloaded as the auth token for the API call.

Once you have created the service account, you need to extract the JSON key and store it in your project files. This key will be used later when configuring Auth0 to send data to BigQuery.

Integrating Auth0 with Google BigQuery

Now that we have all we need on the BigQuery side, we’ll need to set up Auth0 actions to integrate with BigQuery. With this integration, you can capture and log user activity data into BigQuery, enabling detailed analysis and reporting on user behavior, access patterns, and security events.

Configuring Auth0 to send data to BigQuery

Navigate to your Auth0 application's Actions section and create a new action. In the Custom action’s event editor, we need to write code that will construct a JSON payload based on the contents of the Event object it to BigQuery using the BigQuery API:

JAVASCRIPT
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const axios = require('axios');




// Define your BigQuery project and dataset information

const projectId = 'your-project-id';

const datasetId = 'your-dataset-id';

const tableId = 'your-table-id';




// Define your BigQuery endpoint

const bigQueryEndpoint = `https://bigquery.googleapis.com/bigquery/v2/projects/${projectId}/datasets/${datasetId}/tables/${tableId}/insertAll`;




// Define the function to send data to BigQuery

async function sendDataToBigQuery(data) {

try {

// Make the API request to BigQuery

const response = await axios.post(bigQueryEndpoint, data, {

headers: {

Authorization: 'Bearer your-auth-token', // Replace with your authentication token

'Content-Type': 'application/json',

},

});




if (response.status === 200) {

console.log('Data sent to BigQuery successfully');

} else {

console.log('Error sending data to BigQuery:', response.data);

}

} catch (error) {

console.error('Error sending data to BigQuery:', error.message);

}

}




// Handle incoming webhook request

exports.onExecutePostLogin = async (event, api) => {




// Verify the request and extract the payload

const payload = event.body;




// Process the webhook data and send to BigQuery

await sendDataToBigQuery(payload);




};

After the action is created, Auth0 will automatically send login data to BigQuery whenever a user logs in to your application. This makes it easy to keep your BigQuery database up-to-date with the latest user information.

To learn more about the different flows that can be triggered from Auth0, refer to the Auth0 Action flow use case examples in the docs.

Testing the Integration

Once you have configured Auth0 to send data to BigQuery, you can confirm that the integration is operational by navigating to your BigQuery table in the Google Cloud Console and checking for new data. If data is present, then the data is flowing correctly, and the integration is operational.

Analyzing Auth0 data in Google BigQuery

Running basic queries on Auth0 data

Now that you have data flowing from Auth0 to BigQuery, it's time to perform some basic analytics. BigQuery provides a web UI that you can use to run SQL queries against data stored in your tables. You can create queries to find trends, examine user activities and so much more.

Creating custom reports and visualizations

BigQuery integrates with various Business Intelligence (BI) tools like Tableau or Looker to provide customized reports and visualizations. This data can also be joined with data ingested from other data sources using CDPs and Data warehouse tools.

These tools can help you create insightful visualizations such as line charts, heat maps, pie charts, and more, enabling you to effectively communicate your data insights.

Exporting data for further analysis

You can also export data from BigQuery to other tools like Google Sheets or Excel using the built-in export functionality. This feature is useful when you want to perform more in-depth or granular analysis of your data. You can also export data in different file formats like CSV or JSON to integrate with other non-Google data management platforms.

Conclusion

The integration of Auth0 with Google BigQuery is a potent tool for extracting insights from your user data. By following the steps outlined in this article, you can easily connect Auth0 and BigQuery to unlock the full potential of your data. As businesses continue to face new challenges in data management and analysis, they can rely on tools such as Auth0 and BigQuery to stay ahead of the curve and make better-informed decisions.