--- sourceDocument: Yokohama Enable AI sourceDocumentLink: https://servicenow-prod.fluidtopics.net/r/yokohama/intelligent-experiences Release : - yokohama ft:locale : - en-US ft:publication_title : - Yokohama Enable AI ft:clusterId : - platai bundleId : - platai workflow : - Platform --- # Data normalization # Data normalization {#ariaid-title1} Release version: Yokohama Updated January 30, 2025 ![](https://www.servicenow.com/docs/portal-asset/ico-clock) 2 minutes to read Summarize ![AI sparkle icon](https://servicenow.com/docs/portal-asset/ai-sparkle-icon) Summarized using AI This content was generated using new OpenAI-powered functionality. Results are provided on an as is basis and are not guaranteed to be accurate or complete. ## Summary of Data normalization Data normalization in ServiceNow's Document Intelligence standardizes extracted data into consistent formats across all fields. This process enhances data usability by enabling easier grouping, analysis, and integration with other applications on the ServiceNow AI Platform. Show full answer Show less ## Supported Field Types The normalization process converts several field types to standard formats: * **Date:** Converted to a standard format such as YYYY-MM-DD. * **Reference fields:** Matched against a reference table to ensure consistency. For example, a Vendor field is matched to the corresponding company name in a reference table. * **Integer:** Whole numbers like 12. * **Decimal:** Numbers with up to two decimal places, e.g., 12.5. * **Floating point number:** Numbers with up to seven decimal places, e.g., 12.0000000. These conversions help maintain data integrity and consistency across document processing tasks. ## Data Display and Editing Normalized data is displayed alongside the extracted field values. Users can manually adjust converted values if necessary, such as correcting misread characters in dates (e.g., letter "O" misread as zero). ## Handling Ambiguous Data When extracted data can be interpreted in multiple ways, Document Intelligence uses default settings defined in the use case configuration to resolve ambiguity. For example, the default date format preference (month-first or day-first) dictates how ambiguous dates are converted. Users may need to review and confirm these interpretations during document tasks, and automated processing can pause to ensure accuracy depending on configuration. Certain types of data extracted from documents are converted into a standard format so that they appear the same across all fields. This process increases the usefulness of the data by enabling it to be grouped and analyzed more easily. It also supports integration with other applications on the ServiceNow AI Platform. ## Field types {#data-normalization__section_ggb_ysl_rxb} The following field types are converted to support data normalization: {#data-normalization__table_qbs_lsl_rxb__entry__2} | Field type | Description | |-|-| | Date | Standard date format. For example, YYYY-MM-DD. | | Reference field | A field that uses a field in another table as a standard. DocIntel matches the extracted data to the standard. For example, a use case has a reference field called Vendor that points to the Name column in the Company table as the reference. When processing a document task, DocIntel extracts "Degas Dairy Products, Inc" from the document and fills the Vendor field with that value. DocIntel compares the value to the company names in the reference table and finds "Degas Dairy Products, Inc" as a match. In the document task, "Degas Dairy Products, Inc" is matched to "Degas Dairy Products, Inc" in the reference. | | Integer | Whole number. For example, 12. | | Decimal | Number with up to two decimal places. For example, 12.5 or 12.55. | | Floating point number | Number with up to seven decimal places. For example, 12.0 to 12.0000000. | [ ] {#data-normalization__table_qbs_lsl_rxb} To set the field type, see [Create a field for data extraction](https://servicenow-prod.fluidtopics.net/RubJF3W4Y0T0k8OWs~lVYQ "Set up fields as part of your use case. Document Intelligence uses fields to identify and extract data from documents. Fields can be grouped to help DocIntel extract data from documents with tables, check box lists, and other logical groupings of fields."). ## Display {#data-normalization__section_uqy_ctl_rxb} A completed data extraction field shows the converted value next to it. You can adjust the converted date value by selecting Edit. Note: In some cases, the data extracted from the document may not be in a valid format to be converted. For example, if DocIntel read the letter O instead of a number 0 in a date field (11.12.2o23), then it would not be converted. In this case, edit the field to the correct format. ## Ambiguous data {#data-normalization__section_cxy_r3t_pbc} If there is data in a document that can be understood in more than one way, DocIntel interprets that value based on the default selected for it in the use case configuration. DocIntel must interpret an ambiguous value in order to accurately convert it to the normalized format. For example, a use case has a Date field, and Month first is selected as the default order to interpret ambiguous dates. When a document containing the date 1/2/2024 is processed for the use case, DocIntel interprets that date as January 2, not February 1, when it extracts that value and converts it. In such cases, the user completing a document task may need to confirm or correct the conversion of ambiguous values. Depending on the field's configuration in the use case, automated document processing may be interrupted to ensure the conversion is accurate. **Related concepts** * [Confidence scores](https://servicenow-prod.fluidtopics.net/yWTsGjjlTROPymGptm53Bg "A confidence score is a measurement (percentage) of how reliable DocIntel is in providing a recommendation for a field. The higher the score, the more reliable the recommendation.") * [Document Intelligence terminology](https://servicenow-prod.fluidtopics.net/yuPdcM1zr2AiUJ5~Ls_XjA#docintel-terminology "Before getting started with Document Intelligence (DocIntel), it's important to understand some key concepts used in the application.") * [Languages supported by Document Intelligence](https://servicenow-prod.fluidtopics.net/bOBjNuQ97uyjGXlcDzC67g "The Document Intelligence application provides support for documents in different languages.") **Related reference** * [Components installed with Document Intelligence](https://servicenow-prod.fluidtopics.net/DYyunM8vVjDHIHoN0yyV7g "Several types of components are installed with activation of the Document Intelligence plugin, including tables and user roles.") * [Data extraction modes](https://servicenow-prod.fluidtopics.net/wmLw765ccpyFl7AqzhFZzg "Extraction modes determine how the data is extracted in the document task and how the task is processed. The mode changes the behavior of the fields in the Document Intelligence workspace.") * [Document field statuses](https://servicenow-prod.fluidtopics.net/2biJ4QcheUKKwDrNvYAQfQ "The following is a list of the statuses for fields in DocIntel document tasks. These statuses apply to fields for both document classification and data extraction.") * [Document Intelligence forms](https://servicenow-prod.fluidtopics.net/5_0qq8qk~jOqHeVnryX8jg "Use forms to view and update Document Intelligence information.") * [Document Intelligence properties](https://servicenow-prod.fluidtopics.net/fhT5~56YUNPrTEzeEPh31g "Document Intelligence (DocIntel) system properties control the behavior of the Document Intelligence application.") * [Document Intelligence roles](https://servicenow-prod.fluidtopics.net/5EzRCUEQBBpVOOVyklb9EQ#document-intelligence-user-roles "Document Intelligence is installed with these roles.") * [Document task statuses](https://servicenow-prod.fluidtopics.net/2FAYrKPVns704k0CM3jPdQ "The following is a list of the statuses for DocIntel document tasks. These statuses apply to tasks for both document classification and data extraction.") * [Domain separation and Document Intelligence](https://servicenow-prod.fluidtopics.net/0ImLItHAVzGvlXah~~zacw "This domain separation overview relates to Document Intelligence. Domain separation enables you to separate data, processes, and administrative tasks into logical groupings called domains. You can then control several aspects of this separation, including which users can see and access data.") * [Limitations in Document Intelligence](https://servicenow-prod.fluidtopics.net/pX_jxuElO2MCx3~Mn2NeRQ "There are several important limitations to be aware of when you’re using Document Intelligence. There are also some limitations with Now Assist in Document Intelligence that differ from the limitations in Document Intelligence.")