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Data Quality Management

Minimize the Effort Required for Corrections With High-Quality Data

The symbol consists of a blue square with rounded corners and shows a stylized palm bearing a branched diagram. The diagram consists of four connected nodes in the form of small rectangles, which are arranged by lines to form a tree structure. The symbol stands for the workflow management of crossbase.

Data Quality Management (DQM) checks the completeness of data maintenance based on defined mandatory fields. The check can be performed for individual products or across entire product areas. Mandatory fields are defined either globally or in the context of a specific output, e.g., for the shop, portals, or trade partners. This ensures in advance that all relevant data and translations for the output channels are fully maintained. Data maintenance is supported by progress bars, maintenance wizards, and color-coded labels.

The Benefits

Graphical representation of the completeness of mandatory fields
Checking for completeness with respect to specific output channels
Checking for completeness with respect to languages
Maintenance wizards for guided completion of missing fields
High data quality, resulting in minimal correction effort

Validation of Required and Optional Fields

Mandatory and optional fields are defined in advance on a class-by-class basis:

Attributes or categories for media and text elements can be used as mandatory fields.
With Data Quality Management, users can perform an evaluation of the completeness of data maintenance and translation and visually represent progress for an entire product area.
The missing information can then be added using the maintenance wizard.

Data quality check for a product: Media elements marked as mandatory fields are missing, as are translations into French. Features and text elements are fully maintained.

Checking Output Contexts

The process is similar to that for checking required and optional fields:

Output contexts are specified, and the relevant fields and output structure are defined, as these can vary depending on the output channel (e.g., Shop Europe, Shop USA, CAD Portal, TENDER Portal, etc.).
The output context can be set during data maintenance, and the system can check whether all relevant information for a specific output channel is complete in terms of completeness.
The missing information can then be added using the maintenance wizard.