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Reference dataset

Introduction

The reference dataset has the same structure as a standard dataset, but is used to enrich/insert DTP data. It determines the way in which the source dataset data are transformed before being added to the target dataset.

Once the reference dataset has been created, it is possible to specify the field's reference type, or the scope of the same field in data transformation processes.

Reference type Function
Condition Relates the records of the reference dataset to those of the target dataset.
Attributes Identifies, in the target dataset, the fields to be defined using the reference dataset.
Level Dataset field that defines a level of exception to a behaviour defined in the source dataset. Does not accept null values and the data is numeric.
Source filter Filters the source dataset when entering data, or the target dataset when updating data. The data is text type. Note: the filter type column supports null values. In these cases, the data involved in the enrichment operation are not filtered.

For more details on the level and filter fields, see Enrichment with Reference dataset.

Reference dataset - Deploy

A deploy type reference dataset inherits all the functionalities of a reference dataset, but allows you to create relational logics between the fields of the source dataset and those of the target dataset. These logics define how the data are enriched in the target dataset. Therefore, not only can they be one to one or many to one, like for normal reference datasets, but they can also be one to many or many to many When a source field is related to several fields of the target dataset, during the operation the deploy reference dataset adds all the necessary rows to the target dataset table.

Note: If the reference has a null value for a column used as a condition, it will never be fulfilled.

Reference dataset - advanced settings

An advanced settings dataset inherits all the functionalities of a reference dataset, but allows you to define advanced conditions for the enrichment operations. In particular, it allows you to specify multiple comparison requirements (e.g. value of the condition: "<>X" or "=A,B,C") to be verified to satisfy the condition on the target dataset values.

The supported elements are listed below:

  • Values like <>X, in which X is a fixed value
  • Null value to indicate that all the values satisfy the condition on the target dataset
  • Filter type field

Elements that are not supported are listed below:

  • Special character %
  • Level type fields
  • Data and number type Condition columns

Reference dataset - Existence

An existence type dataset inherits all the functionalities of a reference dataset. This also allows you to perform existence checks on the target dataset data, piloted by conditions.

The supported elements are listed below:

  • M value: stands for Mandatory, mandatory, the condition will be considered
  • Value null: in this case the condition will NOT be considered

This type of reference dataset can only be used with theexistence check operation.