Normal values

  • Release version: Washingtondc
  • Updated February 1, 2024
  • 2 minutes to read
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    Summary of Normal Values

    Normal values in ServiceNow AI Platform streamline field data by standardizing ambiguous variations into a single, clear value. This process enhances data consistency and improves system performance by addressing issues arising from duplicate values and complex query conditions.

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    Key Features

    • Field Value Variations: Records can originate from automated entries, imports, or manual user input, leading to inconsistent representations of the same data.
    • Aliases: Known variations of a field value can be designated as aliases, allowing for straightforward normalization when a limited number of variants exist.
    • Rules: For extensive or complex variations, rules can be created to define conditions for normalization, utilizing regular expressions for broader matching.
    • Normalized Queries: Administrators can enable normalization in queries, allowing filters to utilize normalized values without losing the context of original conditions.
    • Scripting and Normalization: Scripts that insert or update records automatically apply normalization, ensuring consistency in data entries.

    Key Outcomes

    Implementing normal values allows ServiceNow customers to:

    • Reduce data duplication and enhance search functionality.
    • Simplify database queries and business logic conditions.
    • Create a more coherent and manageable dataset through coalescence of related records.
    • Ensure accurate data representation across the system by applying normalization consistently.

    A normal value replaces similar but ambiguous field values with one standard value.

    Field value variations

    Records values can come from multiple sources such as:
    • Automated entries made by Discovery.
    • Automated entries made by importing records from external systems or files.
    • Manual entries made by users.
    Each of these sources may describe the same field value in several different forms. For example, the CPU Type field on a computer CI form might display any of the following similar values:
    • E3350 (Intel) 4.5.2234
    • Intel Xeon 5.4.554
    • Xeon L3350
    • L3350
    Without normalization, these variant field values results in:
    • Duplicate CPU types
    • Poor search results
    • Complex queries and conditions to apply business logic

    Creating a normal value record solves these issues by consolidating on one standard value such as Xeon.

    Identifying variations with aliases and rules

    Each Normal value record specifies how to identify variations of a normal value using a combination of aliases and rules.

    Aliases

    Aliases are known variations of an input value that normalization converts to the normal value. Use aliases when there is a short list of variant values.

    For example, you could create a normal value Xeon that has these aliases.
    • E3350 (Intel) 4.5.2234
    • Intel Xeon 5.4.554
    • Xeon L3350
    • L3350
    Whenever a normalization data job or normalized query sees a field value matching an alias, it automatically replaces the field value with the normal value. Normalization data jobs and queries process aliases before rules.
    Note:
    Aliases are logically equivalent to rules using the [is] operator in a condition where [Field name][is][Alias value]. For example, the sample aliases are equivalent to these rules: [CPU Type][is][E3350 (Intel) 4.5.2234] OR [CPU Type][is][Intel Xeon 5.4.554] OR [CPU Type][is][Xeon L3350] OR [CPU Type][is][L3350]
    Rules

    Rules specify the conditions under which normalization replaces an input value with the normal value. Use rules when there are a large number of possible variant values, or when you must create complex conditions.

    For example, the normal value Xeon could have this rule.

    [CPU Type][matches regex][.*\bxeon\b.*]

    Whenever a normalization data job or normalized query sees a field value matching a rule, it automatically replaces the field value with the normal value. Normalization data jobs and queries process rules after aliases.

    Rules and aliases can be combined to normalize a field. Make sure to test your normalization methods before applying them to all the existing records in the database.

    Normalized queries

    An administrator can configure normalization to apply to queries issued against normalized fields in lists. Select the Normalize query check box on the Normalization form to enable this functionality. In a list containing normalized values, Filters and breadcrumbs using the original (raw) value for the normalized field in the query condition.

    Figure 1. Normalized query example

    The filtered list returns records with the normal value substituted for the raw value. However, the breadcrumbs for the filter display the original query conditions.

    Figure 2. Normalized query results

    Scripting and normalization

    Scripts that update or insert records into the database (GlideRecord) are normalized automatically when field normalization is applied. For example, if a script to insert a CI record contains a CPU type of Xeon L3350, the script is normalized to insert the CI with a CPU type of Xeon instead. Scripts that query the database for normalized field values (using the conditions of equals or not equals) can be configured to return the normal value (such as Xeon) rather than the original (raw) value.