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Interface Mapping Adoption Guide
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.

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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

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.

Table 1. CDM Onboarding Lifecycle
Phase	Activity	MID Role
1 – Discovery	Source system inventory, data profiling, sample data review	Input gathered for pre-requisite checklist
2 – Design	CDM subject area selection, interface mapping, transformation design	MID is actively completed during this phase
3 – Review	Business sign-off, architect validation, DQ rule confirmation	MID reviewed and finalised; gaps resolved
4 – Engineering	Metadata loading, ETL code generation, DDL deployment	MID is consumed as primary specification input
5 – Testing	Data validation, reconciliation counts, DQ checks	MID used as expected-behaviour reference
6 – Go-Live	Production cutover, monitoring, hypercare	MID archived as system-of-record for lineage