Welcome
Interface Mapping Adoption Guide
Review and Sign-off Process
The mapping is not complete until all three sign-off gates have been passed. The order matters — do not request engineering sign-off before business sign-off.

HCL MaxAI CDM Documentation
Release Notes
Installation Guide
User Guide
Ops Guide
Interface Mapping Adoption Guide
- Introduction
  This Adoption Guide explains, in plain language, how to perform that mapping exercise end-to-end, from understanding your source data all the way to validated, signed-off mapping rows ready for metadata loading and ETL generation.
- Why Interface Mapping Matters
  A CDM onboarding project can only succeed if the mapping exercise is done well. Poor mapping has cascading effects across data quality, ETL generation, analytics, compliance, timeline, and MaxAI readiness.
- Where It Fits in CDM Onboarding
  CDM onboarding follows a structured lifecycle. The interface mapping exercise sits at the heart of the Discovery and Design phase — after source understanding and before any ETL or DDL is generated.
- Roles and Responsibilities
  The mapping exercise requires involvement from five key roles, each bringing specific expertise and perspective to ensure the exercise is complete and correct.
- Pre-requisites Before Mapping Starts
  Do not open the MID until the following artefacts have been collected from the client. Attempting to map without these leads to guesswork and rework.
- Understanding CDM Subject Areas
  You do not need to know the full CDM model in detail before starting. Use the subject area guide to identify which family of LDZ tables your source data likely belongs to.
- Mapping Principles
  These principles must guide every mapping decision. Violating them leads to data quality problems, ETL complexity, and rework.
- Step-by-Step Mapping Method
  Follow all eight steps in sequence for each source system in scope. Do not skip steps to save time — each step produces decisions that the next step depends on.
- How to Choose the Right Target Table
  Use this decision guide when you are unsure which CDM entity to target. Work through the questions from top to bottom and stop at the first match.
- Common Mapping Patterns
  The following patterns appear in almost every CDM onboarding engagement. Recognising the pattern early saves significant time.
- Worked Examples
  The following worked examples use a fictional retail bank, "Horizon Bank", which is onboarding its core banking data into CDM.
- Data Quality and PII Guidance
  Every mapping row in the MID should have at least one data quality rule. Every source column containing personally identifiable information must be flagged in the PII column.
- Handling Gaps and Extensions
  Not every source field will have a direct target in the standard CDM model. Follow a hierarchy of options before raising an extension request.
- Review and Sign-off Process
  The mapping is not complete until all three sign-off gates have been passed. The order matters — do not request engineering sign-off before business sign-off.
- Debugging and Validation Steps
  After the first ETL run, use the following structured debugging checklist to validate that data has loaded correctly from source to LDZ. Work through each check in sequence.
- Common Errors and FAQ
  This section addresses frequently encountered issues during the mapping exercise and provides remediation approaches.
- Final Checklist
  Use this checklist to confirm that the mapping exercise is complete and the MID is ready for handoff to engineering. Every item must be checked before sign-off.
CDM Redbook

Review and Sign-off Process

The mapping is not complete until all three sign-off gates have been passed. The order matters — do not request engineering sign-off before business sign-off.

Table 1. Sign-off Gates and Reviewers
Gate	Reviewer	What they validate	Sign-off format
1 – Business	Business stakeholder or data steward	Semantic correctness: do the mapped field descriptions match the business intent? Are code conversions correct? Are business rules accurately captured?	Named sign-off in MID VERSION_HISTORY tab
2 – Architecture	CDM data architect	Canonical fit: are the target entity choices correct? Are relationship entities properly separated? Are extension requests appropriate?	Named sign-off in MID VERSION_HISTORY tab
3 – Engineering	ETL lead or data engineer	Implementability: are all transformations technically feasible? Are source connections available? Are DQ rules implementable in the ETL framework?	Named sign-off in MID VERSION_HISTORY tab

After all three gates are passed, increment the MID version number (e.g., V1.0 → V1.1) and record the change in the VERSION_HISTORY tab. The signed-off MID is then formally handed to the engineering team for metadata loading.