MDM Data Governance & Quality Management 4 — Questions and Answers
Question 1: When Informatica MDM evaluates survivorship rules and two sources have identical trust scores for the same attribute, what is the typical tiebreaker?
- The most recently updated source value wins based on the last-update timestamp (Correct answer)
- The record with the higher match score wins
- The record from the primary source system always wins
- A random selection is made and logged for steward review
Correct answer: The most recently updated source value wins based on the last-update timestamp
When trust scores are equal, MDM Hub defaults to selecting the most recently updated value, using the source record's last-update timestamp as the tiebreaker.
Question 2: Which Informatica MDM data quality dimension is violated when the same customer appears twice with different email addresses in the golden record store?
- Uniqueness (Correct answer)
- Accuracy
- Completeness
- Timeliness
Correct answer: Uniqueness
Duplicate master records violate the uniqueness dimension because each real-world entity should be represented exactly once in the master data store.
Question 3: A governance policy requires that changes to supplier master records be approved by at least two stewards. Which Informatica MDM feature supports this requirement?
- Multi-step task workflow with sequential approvals in Data Director (Correct answer)
- Dual-source trust scoring with override locking
- Batch job chaining with approval flags in the Batch Viewer
- Schema Manager role-based column masking
Correct answer: Multi-step task workflow with sequential approvals in Data Director
MDM Hub's task workflow engine in Data Director can be configured with multi-step, multi-approver sequences to enforce dual-approval governance policies.
Question 4: In Informatica MDM, what is the consequence of setting a match column's search level to 'Exact' instead of 'Fuzzy'?
- Only records with identical values for that column are considered potential matches, reducing false positives but potentially missing true duplicates (Correct answer)
- The column is excluded from the match key and ignored during comparison
- All records are treated as duplicates regardless of their values
- The column is used only for cleansing, not matching
Correct answer: Only records with identical values for that column are considered potential matches, reducing false positives but potentially missing true duplicates
An 'Exact' match level requires character-for-character equality, which increases precision but may miss true matches with minor variations like typos.
Question 5: Which Informatica MDM governance mechanism prevents a source system from overwriting a steward-approved value with a lower-quality incoming update?
- Manual override and trust score locking on specific attributes (Correct answer)
- Reject table routing for all updates from that source
- Disabling the source system's landing table feed
- Setting the base object to read-only mode
Correct answer: Manual override and trust score locking on specific attributes
Stewards can manually lock specific attribute values in the golden record, preventing lower-trust source updates from overwriting curated, approved data.
Question 6: What is the difference between a 'hard merge' and a 'soft merge' in Informatica MDM's master data governance?
- A hard merge permanently consolidates records into one golden record while a soft merge links records but preserves their separate identities (Correct answer)
- A hard merge skips data quality checks while a soft merge applies all cleanse rules
- A hard merge is batch-only while a soft merge is real-time only
- A hard merge applies to person records while a soft merge applies to organization records
Correct answer: A hard merge permanently consolidates records into one golden record while a soft merge links records but preserves their separate identities
Hard merges create a single unified golden record from duplicates, whereas soft merges create a cross-reference link while keeping the source records individually identifiable.
Question 7: In the context of Informatica MDM data governance, what does 'data lineage' specifically track?
- The origin source system and transformation history of each attribute value in the golden record (Correct answer)
- The list of downstream applications that consume master data via SIF APIs
- The sequence of batch jobs that processed a record through the MDM pipeline
- The hierarchy relationships between parent and child entities in the data model
Correct answer: The origin source system and transformation history of each attribute value in the golden record
Data lineage in MDM tracks where each golden record attribute came from, including which source system contributed it and what transformations were applied.
MDM Data Governance & Quality Management 4
When Informatica MDM evaluates survivorship rules and two sources have identical trust scores for the same attribute, what is the typical tiebreaker?