Normalize and standardize fields using Gio™ AI Assistant - Precisely Data Integrity Suite

Data Integrity Suite

Product
Spatial_Analytics
Data_Integration
Data_Enrichment
Data_Governance
Precisely_Data_Integrity_Suite
geo_addressing_1
Data_Observability
Data_Quality
dis_core_foundation
Services
Spatial Analytics
Data Integration
Data Enrichment
Data Governance
Geo Addressing
Data Observability
Data Quality
Core Foundation
ft:title
Data Integrity Suite
ft:locale
en-US
PublicationType
pt_product_guide
copyrightfirst
2000
copyrightlast
2026

Clean and prepare data by making field values consistent and standardized across your dataset.

This agent can perform the following tasks:

  • Normalize fields (for example, country names, codes, city names)
  • Standardize date formats
  • Standardize and verify address fields
  • Apply custom coding for advanced normalization (for example, metro/non-metro classification)
  • Ensure data correctness against business rules
  1. Select or create a pipeline (for example, Property_Policy_Holders).
  2. In the pipeline canvas, click Gio™ AI Assistant to view its panel.
  3. Select one of the following options to start the agent:
    • Normalize Fields: For making field values consistent (for example, fixing typos, standardizing codes).
    • Standardize Fields: For enforcing a single, correct format (for example, date formats).
    • Enrich Spatial Data: For adding spatial information (optional).
  4. Type your request in the input box so the agent can analyze the dataset and suggest recommended steps.

    For example, type: "I want to standardize the Date, Country, state, addresses fields in this dataset."

  5. Review the Recommended Steps flowchart and a detailed Steps and Reasoning table displayed by the agent.

    Each step includes a reasoning column that explains its purpose, as shown in the following examples:

    • Standardize Field: Converts country values to 3-letter ISO codes, flags unmapped values.
    • Standardize Date: Parses and outputs dates in a single format (YYYY-MM-DD), flags invalid or out-of-range values.
    • Verify Address: Standardizes and validates address fields for consistency and accuracy.
    • Custom Coding: Normalizes city names, classifies metro/non-metro, flags unmatched entries.
  6. Click Add Steps to insert the recommended steps into your pipeline.
  7. Optional: You can ask the agent to add further steps, such as: "Help me to add a step to ensure correctness of the data against business rules."

    The agent creates a new suggestion that includes the additional steps and the earlier recommendation (for example, additional standardization or validation).

Your quality pipeline now includes normalization and standardization steps configured by the agent. You can run the pipeline to clean and standardize your dataset.

Use cases

  • Country normalization: Converts "INDIA", "india", "IND" to "IND" (ISO3), flags unmapped values.
  • Date standardization: Converts "15/03/1985", "22-07-90", "1988/11/08" to YYYY-MM-DD.
  • Address verification: Standardizes and validates address fields for matching and enrichment.
  • Business rule validation: Adds steps to check data correctness against defined business rules.