Build Sage 300-Connected Visualizations in datapine

datapine is a browser-based business intelligence platform. When paired with the CData Connect AI, you get access to your Sage 300 data directly from your datapine visualizations and dashboards. This article describes connecting to Sage 300 in CData Connect AI and building a simple Sage 300-connected visualization in datapine.

CData Connect AI provides a pure SQL Server interface for Sage 300, allowing you to query data from Sage 300 without replicating the data to a natively supported database. Using optimized data processing out of the box, CData Connect AI pushes all supported SQL operations (filters, JOINs, etc.) directly to Sage 300, leveraging server-side processing to return the requested Sage 300 data quickly.

Configure Sage 300 Connectivity for datapine

Connectivity to Sage 300 from datapine is made possible through CData Connect AI. To work with Sage 300 data from datapine, we start by creating and configuring a Sage 300 connection.

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

2. Select "Sage 300" from the Add Connection panel

3. Enter the necessary authentication properties to connect to Sage 300.

   Sage 300 requires some initial setup in order to communicate over the Sage 300 Web API.

   • Set up the security groups for the Sage 300 user. Give the Sage 300 user access to the option under Security Groups (per each module required).
   • Edit both web.config files in the /Online/Web and /Online/WebApi folders; change the key AllowWebApiAccessForAdmin to true. Restart the webAPI app-pool for the settings to take.
   • Once the user access is configured, click https://server/Sage300WebApi/ to ensure access to the web API.

   Authenticate to Sage 300 using Basic authentication.

   Connect Using Basic Authentication

   You must provide values for the following properties to successfully authenticate to Sage 300. Note that the provider reuses the session opened by Sage 300 using cookies. This means that your credentials are used only on the first request to open the session. After that, cookies returned from Sage 300 are used for authentication.

   • Url: Set this to the url of the server hosting Sage 300. Construct a URL for the Sage 300 Web API as follows: {protocol}://{host-application-path}/v{version}/{tenant}/ For example, http://localhost/Sage300WebApi/v1.0/-/.
   • User: Set this to the username of your account.
   • Password: Set this to the password of your account.
   
4. Click Save & Test
5. Navigate to the Permissions tab in the Add Sage 300 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 Sage 300 data from datapine.

Connecting to Sage 300 from datapine

Once you configure your connection to Sage 300 in Connect AI, you are ready to connect to Sage 300 from datapine.

1. Log into datapine
2. Click Connect to navigate to the "Connect" page
3. Select MS SQL Server as the data source
4. In the Integration step, fill in the connection properties and click "Save and Proceed"
   • Set the Internal Name
   • Set Database Name to the name of the connection we just configured (e.g. Sage3001)
   • Set Host / IP to "tds.cdata.com"
   • Set Username to your Connect AI username (e.g. [email protected])
   • Set Password to the corresponding PAT
   • Set Database Port to "14333"
   
5. In the Data Schema step, select the tables and fields to visualize and click "Save and Proceed"
6. In the References step, define any relationships between your selected tables and click "Save and Proceed"
7. In the Data Transfer step, click "Go to Analyzer"

Visualize Sage 300 Data in datapine

After connecting to CData Connect AI, you are ready to visualize your Sage 300 data in datapine. Simply select the dimensions and measures you wish to visualize!

Having connect to Sage 300 from datapine, you are now able to visualize and analyze real-time Sage 300 data no matter where you are. To get live data access to hundreds of SaaS, Big Data, and NoSQL sources directly from datapine, try CData Connect AI today!