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Status Future consideration
Workspace Knowledge Catalog
Created by Guest
Created on Sep 9, 2024

Automated Data Mapping for RDM Data Imports

Problem Statement: Currently, IKC-RDM requires manual mapping of data elements to their corresponding column names and data types when importing data from files like CSV, XML, or JSON. This can be time-consuming and error-prone, especially for datasets with many columns.

Proposed Solution: Implement an automated data mapping feature that can intelligently map data elements to their corresponding column names and data types based on data characteristics and schema information.

Function Requirements:

  • Header-Based Mapping: Automatically map data elements to column names based on the header row of a CSV file.

  • Schema-Based Mapping: Leverage schema information (e.g., XML schema, JSON schema) to map data elements to their corresponding fields.

  • Data Type Inference: Automatically infer the data type of each data element based on its value and context.

  • Manual Overrides: Allow for manual overrides of the automated mapping if necessary.

Benefits of Automated Data Mapping:

  • Efficiency: Significantly reduce the time and effort required for data mapping.

  • Accuracy: Improve data accuracy by minimizing manual errors.

  • Consistency: Ensure consistent mapping across different datasets.

  • Productivity: Enable users to focus on data analysis and transformation rather than manual mapping tasks.

Needed By Quarter
  • Admin
    Michal Szylar
    Reply
    |
    Dec 11, 2024

    Hello,
    This idea makes a lot of sense, but we don't have a committed date at this time (likely 2025). We will update the status as soon as it is added to the roadmap.

    Best regards,