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  1. Preface
  2. Introduction to Reference Data
  3. Reference Tables in the Analyst Tool
  4. Reference Data in the Developer Tool
  5. Classifier Models
  6. Probabilistic Models
  7. Appendix A: Reference Data and Informatica Data Engineering Integration

Reference Data Guide

Reference Data Guide

Probabilistic Model Label Data

Probabilistic Model Label Data

The label values in a probabilistic model represent the types of information that the reference data values might contain. When you add reference data rows to a model, assign a label to each value in each row. The labels that you add to the model appear in the Label view and in the menu options in the Data view.
You can assign any label in the model to any reference data value. If the same value has different meanings in different rows of reference data, you can assign a different label to each value in each row.
The range of label values can correspond to the range of input ports that the Labeler transformation or the Parser transformation reads during probabilistic analysis. The probabilistic model must contain at least one label value that the transformation can apply to the data values on each input port.
For example, a warehouse might store inventory data in a comma-delimited file that defines eight columns. You design a mapping that parses the inventory data to a database table. You create a probabilistic model with a label value for each data column. When you run the mapping, the Parser transformation writes each value in the input data to the correct column in the target table.
The following table shows the columns of inventory data and the label values that you might create in a probabilistic model:
Inventory Column Name
Label Name
Product_Name
Product_Name
Quantity
Quantity
Location
Location
Barcode
Barcode
SKU
Stock_Keeping_Unit
Arrival_Date
Arrival_Date
Cost_Price
Cost_Price
You can use the input column names, or you can use other names. The names do not need to match.

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