Data Mapping & Transformation Flashcards
7 cards from real CSI practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.
Read the first 7 Data Mapping & Transformation flashcards as text
What is 'data normalization' in the context of data transformation?
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.
In JSON-to-XML transformation, which mechanism is most commonly used in integration middleware?
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.
Which strategy resolves conflicts when the same entity appears with different attribute values in two source systems being merged?
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.
A transformation that replaces sensitive data with a format-preserving but fictitious value is called:
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.
What does a 'lookup transformation' do in a data integration pipeline?
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.
Which serialization format is most efficient for high-throughput, schema-enforced data streaming transformations?
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.
In data mapping, a 'derived field' is best described as:
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.