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  • Data Quality checks in PIM

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    Hello

    Today's post discusses about the relevance of quality of data in PIM and its need for easier identification and categorization of data from different sources.

    Data quality checks

    Quality of data plays a very important role in product data management. The data in PIM is accumulated from multiple sources making it essential to optimize the data quality at accepted intervals.

     

    What does data quality mean?

    There are different criterion to identify the quality of data:

    • Correctness: The data must represent the authentic condition.
    • Consistency: There should be no conflict in the data record within self or with other data
    • Reliability: The basis of the data must be crystal-clear.
    • Completeness: A data record must contain all the necessary attributes.
    • Accuracy: The data must have the required degree of precision.
    • Up-to-datedness: All data records must represent the current situation of reality.
    • Freedom from redundancy: There must not be any duplication within the data records.
    • Relevance: The information provided by data records must correspond to the information required.
    • Uniformity: The information in a data record must have a uniform composition.
    • Unambiguity: Every data record must allow explicit interpretation.

     

    For the purpose of ensuring the data quality a Informatica Data Quality component has been integrated into the PIM Desktop.

     

    Creating quality rules

    All rules for quality checks are created and edited using the Data quality perspective. This is called up by selecting Perspective > Open > Management > Data quality. The Data quality configuration tab is active by default and provides the required environment.

    All fields followed by a "*" are mandatory fields in which an entry must be made.

    Data records preceded by a "*" are being edited. Saving is carried out automatically when user exits the view but can also be carried out explicitly manually at any time.

     

    Creating new check categories: To create a new category:

    1. Click on the icon to open input area for creating new category.
    2. Enter a name and a brief description in the corresponding fields.
    3. Click on save icon to confirm the entries or the delete icon to discard them.

     

    Creating new rule groups: To create new rules:

    1. Select a category in the Data quality configuration view.
    2. Click on icon to create new rule group.
    3. Enter a name and a brief description in the corresponding fields.
    4. Specify the data type and therefore the object for which the rule group will apply.
    5. Click on save icon to confirm the entries or the delete icon to discard them.

     

    Creating new rules: To create new rules:

    1. Select a group in the Data quality configuration view.
    2. Click on icon to create new rule .
    3. Enter a name and a brief description in the corresponding fields.
    4. Open the selection dialog box. The dialog box provides the option of selecting from existing rules. All configured parameters are displayed. User can also add own rules and any required reference files.
    5. Select the relevant entry and confirm with OK.
    6. All settings for the selected rule are applied.
    7. The outputs themselves can be directly assigned to fields.
    8. Click on save icon to confirm the entries or the delete icon to discard them.

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