MDM Data Modeling & Master Data Architecture 4 — Questions and Answers
Question 1: Which MDM deployment style is characterized by each source system maintaining its own copy of master data while the MDM hub propagates updates?
- Registry style
- Consolidation style
- Coexistence style (Correct answer)
- Centralized style
Correct answer: Coexistence style
In the coexistence style, source systems retain their own master data copies but synchronize with the MDM hub, allowing gradual adoption.
Question 2: In Informatica MDM, what is a 'match rule set' and how does it differ from an individual 'match column'?
- A match rule set defines the overall scoring threshold, while a match column is a single attribute comparison
- A match rule set groups multiple match columns into a logical combination that must collectively satisfy a match, while a match column is a single attribute comparison (Correct answer)
- A match rule set applies only to fuzzy matching, while match columns apply to exact matching
- A match rule set is used only for manual merge, while match columns are used for automatic merge
Correct answer: A match rule set groups multiple match columns into a logical combination that must collectively satisfy a match, while a match column is a single attribute comparison
A match rule set combines multiple match columns with AND/OR logic to define a compound matching strategy, while individual match columns specify single-field comparison methods.
Question 3: Which type of MDM architecture would be most appropriate for an organization that wants to enrich master data without altering source system records?
- Transactional MDM
- Analytical MDM (Correct answer)
- Operational MDM with write-back
- Registry-only MDM
Correct answer: Analytical MDM
Analytical MDM focuses on creating enriched, consolidated master data for reporting and analytics without modifying source system records.
Question 4: What is the function of 'tokenization' in Informatica MDM's matching framework?
- Encrypting sensitive PII fields before storing in the hub
- Generating standardized match keys from attribute values to improve matching performance and accuracy (Correct answer)
- Replacing real data with synthetic values for testing
- Creating unique identifiers for each source system record
Correct answer: Generating standardized match keys from attribute values to improve matching performance and accuracy
Tokenization in MDM generates match tokens (standardized keys) from attributes like name and address, allowing efficient indexing and comparison during the match process.
Question 5: In Informatica MDM Hub, what is the difference between a 'hard merge' and a 'soft merge'?
- Hard merge permanently merges records with no undo; soft merge marks records as merged but preserves unmerge capability (Correct answer)
- Hard merge is system-initiated; soft merge is human-initiated via Data Director
- Hard merge applies to exact matches; soft merge applies to fuzzy matches
- Hard merge updates source systems; soft merge updates only the hub
Correct answer: Hard merge permanently merges records with no undo; soft merge marks records as merged but preserves unmerge capability
A hard merge permanently consolidates records in the hub, while a soft (manual) merge can be undone via unmerge operations in Data Director.
Question 6: Which modeling concept ensures that a single customer entity in MDM can be associated with multiple addresses (home, work, billing) without data redundancy?
- One-to-one relationship
- Many-to-many relationship table
- One-to-many child object (e.g., Address child object linked to Customer base object) (Correct answer)
- Denormalized flat base object with address columns
Correct answer: One-to-many child object (e.g., Address child object linked to Customer base object)
A child object linked via a one-to-many relationship allows a single customer master record to have multiple associated address records without repeating customer data.
Question 7: What is the purpose of 'period-based hierarchy versioning' in Informatica MDM hierarchy management?
- To archive inactive hierarchy nodes after a retention period
- To record how organizational or product hierarchies change over time with effective date ranges (Correct answer)
- To version the MDM schema when new base objects are added
- To track which version of a match rule set was used during processing
Correct answer: To record how organizational or product hierarchies change over time with effective date ranges
Period-based versioning captures historical hierarchy structures by associating start and end dates with each relationship node, enabling time-travel queries.
MDM Data Modeling & Master Data Architecture 4
Which MDM deployment style is characterized by each source system maintaining its own copy of master data while the MDM hub propagates updates?