Data Migration Requirements Capture

Introduction

• Presenter: Sashina Menel, Founder of Business Analysis Hub
• Focus: Step-by-step process for capturing and documenting data migration requirements.

Key Challenges for Business Analysts

• Absence of User Interface:
  • Business analysts struggle to document requirements without user interfaces.
  • Functional Requirement Documents usually include screen mockups, which are missing in data migration projects.

Step-by-Step Process for Data Migration

1. Data Analysis

• Importance: Identify data discrepancies, bad data, and missing data.
• Common issues:
  • Lack of validations in previous applications leading to bad data accumulation.
  • Mandatory fields left blank or filled with junk data.

2. Discussion with Customer

• Analyze findings and discuss with the customer.
• Possible actions include:
  • Deleting records with bad data.
  • Replacing old values with new ones.
  • Adding new values for missing data.

3. Data Mapping Table

• Purpose: Clarify source data modifications and new target data to be injected.
• Includes business rules for technical team guidance on modifying data sets.
• Example:
  • Update all records for Europe region contacts to a new contact name.
• Important for documenting the format and necessary updates for technical migration.

4. Functional Requirements Specs Template

• Modify existing templates to reflect data migration requirements.
• Include a section for the data mapping table and any additional technical information needed.

Techniques for Data Migration Projects

1. Interviews:

   • Conduct interviews with stakeholders to gather data migration requirements.

2. Workshops and Brainstorming Sessions:

   • Useful for complex migrations; brings stakeholders together to clarify requirements.

3. Interface Analysis:

   • Understand how data is interfaced with different applications.
   • Important to note that databases may be used across multiple applications.

4. Business Rules Analysis:

   • Create business rules for data modifications, clarifying how changes should be applied.

5. Decision Trees:

   • Useful for depicting conditional changes in data, e.g., eligibility criteria.

Conclusion

• Data migration projects require a strong focus on data rather than user interfaces.
• Understanding data formats and applicable business rules is crucial for success.
• Encouragement to comment on takeaways from the video.