Orchid Connect

Data mapping is a crucial step in the data migration process, involving the definition of relationships as well as translation of data from source systems to the target system. Below is a sample template for a data mapping document:

Data Mapping Document

1. Overview:

  • Data Migration Project: [Project Name]
  • Data Mapping Document Version: [Version Number]
  • Date of Last Update: [Date]

2. Data Entities:

  • List of Source Data Entities and Corresponding Salesforce Entities:
    • Source System: [Name of the existing system]
    • Salesforce: [Name of the Salesforce Object]

3. Data Mapping Table:

Source Field Source Data Type Salesforce Field Salesforce Data Type Transformation Rules Notes
[Source Field 1] [Data Type] [Salesforce Field 1] [Data Type] [Transformation Rules] [Notes]
[Source Field 2] [Data Type] [Salesforce Field 2] [Data Type] [Transformation Rules] [Notes]

4. Transformation Rules:

  • Firstly, define transformation rules for each field as applicable.
  • Secondly, specify any data cleansing or formatting requirements.

5. Relationship Mapping:

  • If applicable, map relationships between different entities.
  • Identify parent-child relationships as well as critical linkages.

6. Default Values:

  • Also, specify default values for Salesforce fields, if applicable.
  • Define rules for handling null or missing values.

7. Data Validation Rules:

  • Define validation rules for each field. Evidently, this will ensure data integrity.
  • Specifically outline conditions for rejecting or flagging records that do not meet validation criteria.

8. Lookup Tables:

  • If using lookup tables, provide details on how values in specific fields will be mapped.
  • Include reference tables for codes or enumerations.

9. Incremental Data Loading:

  • Specify how incremental data loading will be handled, primarily if the migration is performed in multiple phases.

10. Key Migration Considerations:

  • Outline any specific considerations as well as challenges related to data migration.
  • Specifically address how historical data, if relevant, will be handled.

11. Data Ownership and Governance:

  • Specify data ownership for each mapped field or entity.
  • Define governance policies and responsibilities.

12. Security Mapping:

  • If applicable, outline security-related mappings, such as roles and access controls.

13. Data Archiving Strategy:

  • Define the strategy for archiving historical data in Salesforce, if necessary.
  • In addition, specify criteria for archiving records.

14. Data Migration Flow:

  • Provide a high-level overview of the data migration flow, indicating the sequence of activities.

15. Testing Strategy:

  • Outline the testing strategy for data mapping. For example, this may include unit testing, integration testing, and user acceptance testing.

16. Data Migration Schedule:

  • Define the schedule for data migration activities, including start and end dates for each phase.

17. Roles and Responsibilities:

  • Additionally, identify roles and responsibilities for individuals involved in the data mapping process.
  • Specify who is responsible for reviewing and approving the data mapping document.

18. Change Management:

  • Also, outline the process for managing changes to the data mapping document.
  • Specify the approval process for modifications.

19. Document Approval:

  • Lastly, include a section for documenting approvals from relevant stakeholders.

To conclude, this data mapping document provides a structured framework for translating data from source systems to Salesforce. Customizing this template based on the specific requirements and complexities of your organization’s data migration project is essential.

Related Content