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Data Audit node
Last updated: Jan 18, 2024
Data Audit node (SPSS Modeler)

The Data Audit node provides a comprehensive first look at the data that you bring to SPSS Modeler. The data is presented in an interactive, easy-to-read matrix that can be sorted and used to generate full-size graphs.

When you run a Data Audit node, interactive output is generated that includes the following information:

  • Information such as summary statistics, histograms, box plots, bar charts, pie charts, and more that can be useful in gaining a preliminary understanding of the data.
  • Information about outliers, extremes, and missing values.

Using the Data Audit node

The Data Audit node can be attached directly to an Import node or downstream from an instantiated Type node.

Screening or sampling the data. Because an initial audit is effective when dealing with big data, you might use a Sample node to reduce processing time during the initial exploration by selecting only a subset of records. The Data Audit node can also be used with nodes such as Feature Selection and Anomaly Detection in the exploratory stages of analysis.

Figure 1. Data Audit node output example
Data Audit node output example
Note: SPSS Modeler displays the traditional skewness value by default. If you click the graph for more detailed statistics and analysis, both the adjusted skewness value and the traditional skewness value are displayed.
Adjusted Skewness
The adjusted skewness value is calculated by Data View.
Traditional Skewness
The adjusted skewness value is calculated by SPSS Modeler and Python.
Figure 2. Data Audit node output example
Data Audit node output example
Figure 3. Data Audit node output example
Data Audit node output example
Figure 4. Data Audit node output example
Data Audit node output example
Figure 5. Data Audit node output example
Data Audit node output example
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