MDM Data Governance & Quality Management 3 — Questions and Answers
Question 1: In Informatica MDM's data quality lifecycle, which stage comes immediately after standardization and before match/merge?
- Consolidation
- Tokenization (Correct answer)
- Survivorship
- Publication
Correct answer: Tokenization
Tokenization generates match tokens from standardized data, enabling efficient comparison during the match phase before records are merged.
Question 2: A governance committee wants to track who approved a merge of two customer records in Informatica MDM. Which capability provides this audit trail?
- MDM Hub audit logging and history tables (Correct answer)
- Hierarchy Manager lineage view
- Schema Manager version control
- Batch Viewer job log
Correct answer: MDM Hub audit logging and history tables
MDM Hub maintains audit logs and history tables (e.g., _HIST tables) that record every change, approval, and merge action along with the user who performed it.
Question 3: What is the role of a 'data domain' in the context of Informatica MDM governance?
- A logical grouping of related master data entities subject to unified stewardship policies (Correct answer)
- A physical database schema partition used to isolate source system tables
- A network segment that restricts access to MDM Hub services
- A batch job category that groups similar cleanse transformations
Correct answer: A logical grouping of related master data entities subject to unified stewardship policies
A data domain defines a governance boundary around related entities (e.g., Customer, Product) so that consistent policies, ownership, and quality rules can be applied cohesively.
Question 4: Which metric is most directly associated with measuring data completeness in an Informatica MDM golden record?
- Percentage of mandatory attributes populated across all master records (Correct answer)
- Number of source systems contributing to each record
- Trust score assigned to the winning source system
- Total records processed per batch cycle
Correct answer: Percentage of mandatory attributes populated across all master records
Completeness is measured by how many required fields are populated; tracking the fill rate of mandatory attributes directly reflects this dimension.
Question 5: In Informatica MDM Hub, what happens to a record placed in a 'pending' state within the workflow?
- It is held for steward review before being promoted to the base object (Correct answer)
- It is immediately merged with the closest matching golden record
- It is permanently rejected and written to the error log
- It is published to subscribed downstream systems
Correct answer: It is held for steward review before being promoted to the base object
Pending records are routed through a stewardship workflow where a data steward must review and approve them before they affect the master data store.
Question 6: Which Informatica MDM mechanism allows a data governance team to define time-based validity for master data attributes?
- Effective-date columns and timeline management in the base object (Correct answer)
- Match rule weighting by batch load timestamp
- Trust score decay functions applied per source system
- Lookup table versioning in Schema Manager
Correct answer: Effective-date columns and timeline management in the base object
MDM Hub supports effective-date metadata on base object records, enabling governance of which attribute values are valid for a given time period.
Question 7: In a data governance framework layered on top of Informatica MDM, what is the primary purpose of a data glossary?
- To provide agreed-upon business definitions for data elements used in MDM entities (Correct answer)
- To list all MDM Hub table names and their column data types
- To document the ETL mapping logic for each source system feed
- To store match token algorithms for each base object
Correct answer: To provide agreed-upon business definitions for data elements used in MDM entities
A data glossary captures business-agreed definitions, ownership, and context for data terms, ensuring consistent understanding across teams using MDM.
MDM Data Governance & Quality Management 3
In Informatica MDM's data quality lifecycle, which stage comes immediately after standardization and before match/merge?