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Get the Report →How to Seamlessly Import Marketo Data into IBM SPSS Modeler
Integrate Marketo data into IBM SPSS Modeler using the CData ODBC Driver for real-time insights and advanced data analysis.
IBM SPSS Modeler is a powerful data mining and predictive analytics platform that enables organizations to extract valuable insights from their data. By connecting Marketo data data to SPSS Modeler via the CData ODBC Driver for Marketo, 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 Marketo data, enabling seamless data import, preparation, and analysis. With the CData ODBC Driver for Marketo, you can unlock the full potential of your Marketo data data within IBM SPSS Modeler for actionable insights.
Overview
Here is an overview of the steps:
- CONFIGURE THE ODBC DRIVER: Set up a connection to Marketo data in the CData ODBC Driver for Marketo by entering the required connection properties.
- SET UP ODBC CONNECTION IN SPSS MODELER: Establish the ODBC connection within IBM SPSS Modeler by selecting the configured DSN.
- IMPORT AND PROCESS DATA: Import the Marketo data data into SPSS Modeler, then review, filter, transform, and prepare the data for predictive analytics and statistical modeling.
Configure the Marketo DSN Using the CData ODBC Driver
To start, configure the DSN (Data Source Name) for Marketo 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 Marketo data Source and enter the required values to establish a connection:
Both the REST and SOAP APIs are supported and can be chosen by using the Schema property.
For the REST API: The OAuthClientId, OAuthClientSecret, and RESTEndpoint properties, under the OAuth and REST Connection sections, must be set to valid Marketo user credentials.
For the SOAP API: The UserId, EncryptionKey, and SOAPEndpoint properties, under the SOAP Connection section, must be set to valid Marketo user credentials.
See the "Getting Started" chapter of the help documentation for a guide to obtaining these values.
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 Marketo 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 Marketo 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 Marketo Data with CData
With the CData ODBC Driver for Marketo, connecting Marketo 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.