Build Visualizations of Sage 300 Data in Birst

Birst is a cloud business intelligence (BI) tool and analytics platform that helps organizations quickly understand and optimize complex processes. When paired with the CData JDBC Driver for Sage 300, you can connect to live Sage 300 data through the Birst Cloud Agent and build real-time visualizations. In this article, we walk you through, step-by-step, how to connect to Sage 300 using the Cloud Agent and create dynamic reports in Birst.

With powerful data processing capabilities, the CData JDBC Driver offers unmatched performance for live Sage 300 data operations in Birst. When you issue complex SQL queries from Birst to Sage 300, the driver pushes supported SQL operations, like filters and aggregations, directly to Sage 300 and utilizes the embedded SQL Engine to process unsupported operations client-side (often SQL functions and JOIN operations). With built-in dynamic metadata querying, the JDBC driver enables you to visualize and analyze Sage 300 data using native Birst data types.

Configure a JDBC Connection to Sage 300 Data in Birst

Before creating the Birst project, you will need to install the Birst Cloud Agent (in order to work with the installed JDBC Driver). Also, copy the JAR file for the JDBC Driver (and the LIC file, if it exists) to the /drivers/ directory in the installation location for the Cloud Agent.

With the driver and Cloud Agent installed, you are ready to begin.

1. Create a new project in Birst.
2. Name the connection (e.g. CDataSage300).
3. Choose Live Access.
4. Select an agent.
5. Set Database Type to Other.
6. Set SQL Type to MSSQL
7. Set the Connection string.

   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.

   Built-in Connection String Designer

   For assistance in constructing the JDBC URL, use the connection string designer built into the Sage 300 JDBC Driver. Either double-click the JAR file or execute the jar file from the command-line.

   java -jar cdata.jdbc.sage300.jar

   Fill in the connection properties and copy the connection string to the clipboard.

   When you configure the JDBC URL, you may also want to set the Max Rows connection property. This will limit the number of rows returned, which is especially helpful for improving performance when designing reports and visualizations.

   Below is a typical JDBC connection string for Sage 300:

   jdbc:sage300:User=SAMPLE;Password=password;URL=http://127.0.0.1/Sage300WebApi/v1/-/;Company=SAMINC;
8. Set the Driver Name: cdata.jdbc.sage300.Sage300Driver and click Save.

NOTE: Since authentication to Sage 300 is managed from the connection string, you can leave Security Credentials blank.

Configure Sage 300 Data Objects

Now that the connection is configured, we are ready to configure the schema for the dataset, choosing the tables, views, and columns we wish to visualize.

1. Select the Schema (e.g. Sage300).
2. Click on Tables and/or Views to connect to those entities and click Apply.
3. Select the Tables and Columns you want to access and click Done.

With the objects configured, you can perform any data preparation and discover any relationships in your data using the Pronto Prepare and Relate tools.

Build a Visualization

After you prepare your data and define relationships between the connected objects, you are ready to build your visualization.

1. Select the Visualizer tool from the menu.
2. Select Measures & Categories from your objects
3. Select and configure the appropriate visualization for the Measure(s) you selected.

Using the CData JDBC Driver for Sage 300 with the Cloud Agent and Birst, you can easily create robust visualizations and reports on Sage 300 data. Download a free, 30-day trial and start building Birst visualizations today.