MDM Data Integration & Synchronization Techniques 4 — Questions and Answers
Question 1: What is the role of 'tokenization' in Informatica MDM's match process?
- Encrypting sensitive PII fields before storing them in the Hub
- Generating standardized search keys from record attributes to enable efficient matching (Correct answer)
- Converting source system primary keys into Hub-format identifiers
- Compressing large text fields to reduce storage overhead
Correct answer: Generating standardized search keys from record attributes to enable efficient matching
Tokenization generates match tokens (standardized search keys) from record attributes, allowing the match engine to efficiently identify potential duplicate records.
Question 2: An organization wants to synchronize MDM golden records with a Salesforce CRM in near-real-time. Which Informatica capability is best suited for this integration?
- Informatica PowerCenter batch ETL
- Informatica Cloud Data Integration (IICS) with MDM SaaS connector (Correct answer)
- Manual export from Hub Console to CSV
- JDBC direct connection from Salesforce to the Hub database
Correct answer: Informatica Cloud Data Integration (IICS) with MDM SaaS connector
Informatica Cloud Data Integration (IICS) provides pre-built connectors and real-time synchronization capabilities between MDM and cloud applications like Salesforce.
Question 3: In Informatica MDM, what does 'unmerge' allow data stewards to do?
- Permanently delete a golden record and all its source contributors
- Separate previously merged source records back into independent records (Correct answer)
- Undo a trust score reconfiguration applied during the last batch run
- Remove a base object column without affecting existing data
Correct answer: Separate previously merged source records back into independent records
Unmerge allows data stewards to reverse an incorrect merge by separating the source records that were consolidated into a golden record, creating distinct records again.
Question 4: Which MDM Hub configuration controls how frequently the batch consolidation job runs automatically in a scheduled integration scenario?
- The Hub Server's JVM memory settings
- The job scheduler configuration within the MDM Hub or an external scheduler like Control-M (Correct answer)
- The trust framework recalculation interval
- The staging table partition policy
Correct answer: The job scheduler configuration within the MDM Hub or an external scheduler like Control-M
Batch consolidation jobs are scheduled via the MDM Hub's built-in scheduler or an external enterprise scheduler, controlling the frequency of match-merge cycles.
Question 5: When multiple source systems provide the same entity (e.g., a customer), Informatica MDM creates one golden record. What mechanism links the golden record back to all contributing source records?
- The XREF (cross-reference) table (Correct answer)
- The match token index
- The base object partition key
- The staging table's system_name column
Correct answer: The XREF (cross-reference) table
The XREF table stores the cross-references between each golden record's ROWID_OBJECT and the source system records that contributed to it, preserving full data lineage.
Question 6: In Informatica MDM Hub, what is the purpose of 'cleanse functions' applied during the Stage process?
- Removing records that fail referential integrity checks
- Standardizing and normalizing source data values before matching and consolidation (Correct answer)
- Encrypting personally identifiable information at rest
- Converting base object records to JSON format for API publishing
Correct answer: Standardizing and normalizing source data values before matching and consolidation
Cleanse functions standardize source data (e.g., name parsing, address normalization) during staging so that the match engine can accurately identify duplicates.
Question 7: A company uses Informatica MDM for customer data and wants changes to golden records to trigger updates in a downstream data warehouse within minutes. Which approach achieves this?
- Run the full consolidation batch job every night and reload the warehouse daily
- Configure MDM publication events to a message queue consumed by the warehouse ETL in near-real-time (Correct answer)
- Have the warehouse directly query the MDM base object tables via JDBC every hour
- Export golden records to a shared file system and let the warehouse pick them up on a schedule
Correct answer: Configure MDM publication events to a message queue consumed by the warehouse ETL in near-real-time
Publishing golden record change events to a message queue allows the warehouse ETL to consume updates within minutes, achieving near-real-time synchronization.
MDM Data Integration & Synchronization Techniques 4
What is the role of 'tokenization' in Informatica MDM's match process?