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Object Completeness

Object completeness indicators provide information about how complete an object is based on scores that you set for attributes, reference types, data containers, and product to classification link types. While it is possible to calculate a completeness percentage without settings scores for these individual data objects, it is recommended to do so, as you can weigh them based on relevance and outright omit those that should not apply to the overall completeness percentage.

Note: The object completeness functionality is not available on product overrides.

View Completeness Scores

  1. In the Tree, expand the applicable Hierarchy, and then locate the relevant object.
  2. Click the main object tab or the References tab. The Completeness Meter in the upper right corner displays the current status of the object expressed as a percentage.

Note: If no indicator appears it is likely that no completeness scores have been set for the data valid for the object.

  1. Hover the mouse over the Completeness Meter to view a text describing what you can do to improve the completeness percentage.

  1. To get a more detailed view of how the completeness percentage for the selected object is calculated, double-click the Completeness Meter. A Completeness Info window appears, which displays all attributes, data containers, and referenced objects that contribute to the completeness percentage and how they are weighted.

Object completeness indicators are also available in Web UI. See the Object Completeness in Web UI section of the Data Profiling documentation here.

User Privileges

The completeness of an object is always calculated and displayed as if the user had privileges to view and edit all relevant data. However, hints are only provided for data that the user is allowed to edit.

Additionally, this functionality is only accessible to users with the appropriate privileges. For more information, see the Setup Actions section of the System Setup / Super User Guide documentation here.

Define Completeness Scores

For a typical setup, in order to view completeness information, completeness scores must be configured on all relevant attributes, references, data containers, and product to classification link types. This score determines how much to weigh an element of the object when factoring the object's completeness percentage.

Note: For product reference types, images and document reference types, and product to classification link types, the scores are defined on the individual type's main editor.

  1. In System Setup expand Reference Types / Attribute Groups, and then locate the relevant reference type / attribute.
  2. In the Completeness Score field, under the Description section, enter the preferred score. Scores must be integers.

Note: You cannot specify scores for calculated attributes.

Alternatively, when setting the score on the link between a product or classification and a specification attribute, the completeness score of an attribute can be specified on the actual object in the Tree.

  1. In the Tree, expand the applicable hierarchy, and then locate the desired object.
  2. On the References tab, go to Linked Attributes and then click the flipper icon to expand the table.
  3. In the Completeness Score column, enter the preferred score(s) for the relevant attribute links.

Setting Completeness Scores for Data Containers

Unlike other data objects that contribute to the object's completeness percentage, a data container can be incomplete itself, making it possible to contribute only a fraction of its maximum score. The weight of the total possible score of the data container is set on the data container type (just like for attributes and reference types), and any values absent from the individual attributes that comprise the data container are reflected in its score. Additionally, the attributes within a data container can have their own varying scores. In a sense, a data container has its own completeness percentage, and contributes either 100% of its score to the object's completeness percentage, or, if one or more attributes within are missing values, it contributes a fraction of its total possible score.

In the above example, the data container 'Shipping Address' can contribute a total of 15.87% completeness to the object's overall completeness percentage. However, because it has attributes with missing values, it is only contributing 11.11% completeness; roughly 70% of its maximum score.

By viewing the data container itself (pictured above), you can see that the attribute 'Street' is missing a value, which explains why the data container is not contributing 100% of its score. Had all six attributes been weighted with a neutral score, each would contribute roughly 17% to the data container's score. However, based on the completeness breakdown, we know that the attribute 'State' is responsible for roughly 30% of the score. This is because 'State' has a higher weighted score than some of the other attributes.

Note: If a second 'Shipping Address' instance were added, its attributes would be factored in with those of the existing 'Shipping Address' when calculating the score, as they are both held within the same data container.

As with all attributes, the scores for attributes that comprise a data container are defined on the Completeness Score metadata field found on the attributes. The maximum score for the data container itself is defined by the same field on the data container type ('Shipping Address', in this example).

Before completeness scores can be applied to data containers, however, ensure that the Completeness Score attribute is valid for the Data Container Type object type.

Export Completeness Values

Completeness values can be exported to Excel and CSV.

  1. Create a calculated attribute and enter the function "completeness()" in the Value template.

For more information, see the Calculated Attributes section of the System Setup / Super User Guide documentation here.

  1. From the File menu, hover over Export and then click Data....
  2. In Step 4 - Map Data of the Export Manager wizard, add Select Attribute to columns. The Select Attribute or Attribute Group dialog is displayed. Search or browse for the desired calculated attribute.
  3. Select the calculated attribute, check Force calculation, and then continue with the export.

For more information, see the Creating a Data Export section of the Export Manager documentation here.

 

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