Connect to BigQuery Data in ACL Analytics

ACL Analytics, part of Diligent HighBond, is a powerful data analysis software primarily used for audit, risk management, and compliance. It enables professionals to examine and analyze large volumes of data to identify anomalies, trends, and potential risks or fraudulent activities.

CData Connect AI offers a dedicated cloud-to-cloud interface for BigQuery, enabling analytics directly from live BigQuery data within ACL Analytics, all without the need for data replication to a native database. With its inherent optimized data processing capabilities, CData Connect AI efficiently channels all supported SQL operations, including filters and JOINs, directly to BigQuery. This leverages server-side processing to swiftly deliver the requested BigQuery data.

Getting Started

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Configure BigQuery Connectivity for ACL Analytics

Connectivity to BigQuery from ACL Analytics is made possible through CData Connect AI. To work with BigQuery data from ACL Analytics, we start by creating and configuring a BigQuery connection in CData Connect AI.

1. Log into Connect AI, click Sources, and then click Add Connection
👁 Adding a Connection

2. Select "BigQuery" from the Add Connection panel
👁 Selecting a data source

3. Enter the necessary authentication properties to connect to BigQuery. BigQuery uses OAuth to authenticate. Click "Sign in" to authenticate with BigQuery. 👁 Authenticating with OAuth (Salesforce is shown).
   
4. Navigate to the Permissions tab in the Add BigQuery Connection page and update the User-based permissions. 👁 Updating permissions
   

Add a Personal Access Token

When connecting to Connect AI through the REST API, the OData API, or the Virtual SQL Server, a Personal Access Token (PAT) is used to authenticate the connection to Connect AI. It is best practice to create a separate PAT for each service to maintain granularity of access.

1. Click on the Gear icon () at the top right of the Connect AI app to open the settings page.
2. On the Settings page, go to the Access Tokens section and click Create PAT.
3. Give the PAT a name and click Create. 👁 Creating a new PAT
   
4. The personal access token is only visible at creation, so be sure to copy it and store it securely for future use.

With the connection configured and a PAT generated, you are ready to connect to BigQuery data from ACL Analytics.

Connect to BigQuery from ACL Analytics

The steps below outline connecting to CData Connect AI from ACL Analytics to create a new BigQuery data source. The CData Connect AI Virtual SQL Server allows you to establish a connection to your data from integration tools that support connections to SQL servers. The Virtual SQL Server mimics the behavior of a traditional SQL server, and it supports a range of query options.

1. With your Analytics File open, select 'Import' --> 'Database and application' 👁 Creating a new data source
   
2. Create a new connection
3. Set the connection information
   • Server: tds.cdata.com
   • Port: 14333
   • Auth Scheme: Password
   • Username: a Connect AI user, for example, [email protected]
   • Password: the PAT for the above Connect AI user
   • Database: the name of your BigQuery connection, for example, GoogleBigQuery1
   👁 Connecting to Connect AI
   
4. Click "Test Connection"
5. Click "OK"
6. You are now ready to work with your BigQuery data in ACL Analytics! 👁 See your data in ACL Analytics
   

Live connections to BigQuery data from your applications

ACL Analytics can now connect to live BigQuery data directly through Connect AI, allowing you to analyze BigQuery data without duplicating it.

To get live data access to hundreds of SaaS, Big Data, and NoSQL sources directly from your applications, try CData Connect AI today!