CSI Data Mapping & Transformation 3 — Questions and Answers
Question 1: What is 'data normalization' in the context of data transformation?
- Encrypting data fields before loading into a target system
- Restructuring data to reduce redundancy and improve consistency, often conforming values to a standard range or format (Correct answer)
- Compressing data to reduce storage size
- Removing all NULL values from a dataset
Correct answer: Restructuring data to reduce redundancy and improve consistency, often conforming values to a standard range or format
Data normalization reorganizes data to minimize redundancy (database sense) or scales values to a standard range (statistical sense), improving data quality and consistency.
Question 2: In JSON-to-XML transformation, which mechanism is most commonly used in integration middleware?
- Regular expression substitution
- XSLT 3.0 with JSON support or purpose-built middleware converters (Correct answer)
- Binary-to-text Base64 encoding
- SQL CAST functions
Correct answer: XSLT 3.0 with JSON support or purpose-built middleware converters
Modern integration tools use XSLT 3.0 (which natively parses JSON) or dedicated JSON-to-XML converters built into middleware platforms like MuleSoft or Apache Camel.
Question 3: Which strategy resolves conflicts when the same entity appears with different attribute values in two source systems being merged?
- Ignore all records from the secondary source
- Apply a survivorship rule to determine which source's value takes precedence (Correct answer)
- Delete both conflicting records and request manual re-entry
- Concatenate all conflicting values into a single field
Correct answer: Apply a survivorship rule to determine which source's value takes precedence
Survivorship rules define which source system's value 'wins' during master data consolidation, often based on recency, completeness score, or system-of-record priority.
Question 4: A transformation that replaces sensitive data with a format-preserving but fictitious value is called:
- Tokenization
- Data masking (Correct answer)
- Obfuscation hashing
- Field encryption
Correct answer: Data masking
Data masking replaces real sensitive data with realistic but fictitious values, maintaining the format and structure while protecting privacy in non-production environments.
Question 5: What does a 'lookup transformation' do in a data integration pipeline?
- Searches for errors in source data and logs them
- Retrieves reference data from an external table to enrich or validate incoming records (Correct answer)
- Converts all field names to lowercase
- Generates unique sequence numbers for records
Correct answer: Retrieves reference data from an external table to enrich or validate incoming records
A lookup transformation queries a reference or dimension table to enrich incoming records with additional attributes or to validate foreign key values.
Question 6: Which serialization format is most efficient for high-throughput, schema-enforced data streaming transformations?
- CSV with comma delimiters
- Apache Avro with binary encoding (Correct answer)
- HTML with embedded JSON
- YAML with anchors and aliases
Correct answer: Apache Avro with binary encoding
Apache Avro uses binary encoding with an embedded or registry-stored schema, making it compact and fast for high-throughput streaming pipelines like Apache Kafka.
Question 7: In data mapping, a 'derived field' is best described as:
- A field copied directly from the source without modification
- A target field whose value is calculated from one or more source fields using a formula or function (Correct answer)
- A field that is excluded from the target schema
- A field that maps to multiple target columns simultaneously
Correct answer: A target field whose value is calculated from one or more source fields using a formula or function
A derived field is computed during transformation using expressions, functions, or business logic applied to one or more source fields rather than being directly copied.
CSI Data Mapping & Transformation 3
What is 'data normalization' in the context of data transformation?