How to Seamlessly Import Sage 300 Data into IBM SPSS Modeler

IBM SPSS Modeler is a powerful data mining and predictive analytics platform that enables organizations to extract valuable insights from their data. By connecting Sage 300 data data to SPSS Modeler via the CData ODBC Driver for Sage 300, you can leverage real-time access for advanced data mining, predictive modeling, and statistical analysis.

This guide takes you through the steps of connecting IBM SPSS Modeler to Sage 300 data, enabling seamless data import, preparation, and analysis. With the CData ODBC Driver for Sage 300, you can unlock the full potential of your Sage 300 data data within IBM SPSS Modeler for actionable insights.

Overview

Here is an overview of the steps:

1. CONFIGURE THE ODBC DRIVER: Set up a connection to Sage 300 data in the CData ODBC Driver for Sage 300 by entering the required connection properties.
2. SET UP ODBC CONNECTION IN SPSS MODELER: Establish the ODBC connection within IBM SPSS Modeler by selecting the configured DSN.
3. IMPORT AND PROCESS DATA: Import the Sage 300 data data into SPSS Modeler, then review, filter, transform, and prepare the data for predictive analytics and statistical modeling.

Configure the Sage 300 DSN Using the CData ODBC Driver

To start, configure the DSN (Data Source Name) for Sage 300 data in your system using the CData ODBC Driver. Download and install a 30-day free trial with all the features from here.

Once installed, launch the ODBC Data Source Administrator:

• On Windows: Search for ODBC Data Source Administrator in the Start menu and open the application.
• On Mac: Open Applications, go to Utilities, and select ODBC Manager.
• On Linux: Use the command line to launch ODBC Data Source Administrator or use unixODBC if installed.

Once launched, double-click on the CData Sage 300 data Source and enter the required values to establish a connection:

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.

Setup an ODBC Connection in IBM SPSS Modeler

After configuring the DSN, it's time to connect to it in IBM SPSS Modeler:

• Launch IBM SPSS Modeler, log in, and create a new stream.
• From the Sources palette, locate the Database node, and drag it onto the canvas.
• Double-click the Database node to open the configuration dialog. Select , browse to select the configured DSN, then click OK.
• In the Database dialog, browse to select the table(s) you’d like to import, preview the data, and click OK to finalize.

You are now ready to process and analyze the Sage 300 data data in IBM SPSS Modeler.

Process Data: Filter, Categories, and Model

Once the tables are imported, you can refine, filter, categorize, and model your Sage 300 data data in SPSS Modeler:

• Filtering: Double-click your Database connection, go to the Filter section, and select/deselect fields to focus on relevant data. This improves processing speed and model accuracy.
• Set Data Types and Roles: Categorize your fields and assign roles to each data type by navigating to the Types section.
• Perform a Basic Analysis: Drag and drop the Analysis node next to your Database node, connect them, and click the Play button to run the stream and analyze the data.

You have now performed a simple analysis, enabling SPSS Modeler to process and display insights from your database.

Unlock the Potential of Your Sage 300 Data with CData

With the CData ODBC Driver for Sage 300, connecting Sage 300 data data to IBM SPSS Modeler is seamless. Start your free trial today and unlock the full potential of your real-time data for advanced analytics and decision-making.