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
In a real-time streaming integration scenario, which approach minimizes transformation latency?
Answer: Apply stateless, in-line stream transformations using an event-processing engine with no I/O blocking
Stateless in-line stream transformations on engines like Apache Flink or Kafka Streams avoid blocking I/O and disk writes, keeping end-to-end latency in the milliseconds range.
Which mapping technique handles hierarchical source data (e.g., nested JSON) being loaded into a flat relational table?
Answer: Flattening with path-based field extraction
Flattening extracts nested fields using dot-notation or JSONPath expressions and maps them to flat columns in the target table, resolving the hierarchical-to-relational impedance mismatch.
What is a 'dead letter queue' (DLQ) in the context of data transformation pipelines?
Answer: A storage destination for messages that failed transformation and could not be processed successfully
A dead letter queue captures messages that fail transformation due to data quality errors or processing exceptions, allowing them to be reviewed, corrected, and reprocessed without data loss.
When integrating two systems with different character encodings (e.g., UTF-8 vs. ISO-8859-1), which transformation step is critical?
Answer: Explicitly converting character encoding before any string operations are performed
Explicit encoding conversion (e.g., ISO-8859-1 to UTF-8) must occur before any string parsing or manipulation to prevent mojibake and data corruption caused by misinterpreted byte sequences.
What is the primary purpose of a 'data lineage' tool in a complex transformation pipeline?
Answer: To track the origin, movement, and transformations applied to data from source to target for auditability
Data lineage tools record the full journey of data—which source it came from, what transformations were applied, and where it landed—enabling debugging, compliance, and impact analysis.
In a CSI context, 'impedance mismatch' between systems most commonly refers to:
Answer: Structural or semantic differences between source and target data models that complicate direct mapping
Impedance mismatch describes the gap between two systems' data models—such as object-oriented vs. relational, or hierarchical vs. flat—that requires transformation logic to bridge.
Which validation technique ensures referential integrity during data transformation when loading records into a target system?
Answer: Cross-checking foreign key values against the target dimension tables before or during the load
Referential integrity validation cross-references foreign key values in fact or transaction records against already-loaded dimension records to prevent orphaned rows in the target system.