Connect to JD Edwards 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 JD Edwards, enabling analytics directly from live JD Edwards 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 JD Edwards. This leverages server-side processing to swiftly deliver the requested JD Edwards data.

Configure JD Edwards Connectivity for ACL Analytics

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

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

2. Select "JD Edwards" from the Add Connection panel

3. Enter the necessary authentication properties to connect to JD Edwards. Enter the necessary authentication properties to connect to JD Edwards.

   The driver connects to JD Edwards through your Application Interface Services (AIS) Server. Set the following connection properties:

   • URL: The base HTTPS URL of your AIS Server (e.g., https://jde-ais.example.com:8300).
   • User: Your JD Edwards username.
   • Password: Your JD Edwards password.
   • Environment (optional): The JD Edwards environment to use (e.g., PD920 for production or DV920 for development). If not specified, the AIS Server's default environment is used.
   • Role (optional): The JD Edwards role for the session. If not specified, the AIS Server's default role is used.
   • DeviceName (optional): An identifier for the connecting device or application, used for auditing and logging on the AIS Server.
   • Jasserver (optional): The specific Java Application Server (JAS) instance to route requests through, useful in clustered environments.

   Choosing Which Data Is Exposed

   JD Edwards organizes tables and business views by System Code, and the driver exposes each System Code as its own schema. Use these properties to control which schemas are available:

   • DataModel: One or more ERP modules (comma-separated) whose System Codes are exposed as schemas, or All to expose every System Code in the connected instance. Defaults to FinancialManagement.
   • SystemCodes: A comma-separated list of additional System Codes to expose alongside those from DataModel (e.g., 42,43).

   When you connect, the driver sends your credentials to the AIS Server to obtain a session token and caches it. The driver requests a new token automatically before the session expires.

   
4. Click Save & Test
5. Navigate to the Permissions tab in the Add JD Edwards Connection page and update the User-based 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.
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 JD Edwards data from ACL Analytics.

Connect to JD Edwards from ACL Analytics

The steps below outline connecting to CData Connect AI from ACL Analytics to create a new JD Edwards 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'
2. Create a new SQL Server 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 JD Edwards connection, for example, JDEdwards1
   
4. Click "Test Connection"
5. Click "OK"
6. You are now ready to work with your JD Edwards data in ACL Analytics!

Live connections to JD Edwards data from your applications

ACL Analytics can now connect to live JD Edwards data directly through Connect AI, allowing you to analyze JD Edwards 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!