CSI Data Mapping & Transformation 2

Question 1

Which transformation pattern converts a single source record into multiple target records?

Accepted Answer

One-to-many splitting

Answer

One-to-one mapping

Answer

Many-to-one aggregation

Answer

Passthrough transformation

Question 2

In XSLT-based data transformation, what is the primary role of a stylesheet?

Accepted Answer

Defining rules for transforming XML documents into another format

Answer

Storing XML data persistently

Answer

Validating XML against a schema

Answer

Encrypting XML payloads in transit

Question 3

When performing a many-to-one aggregation in data mapping, which operation is most commonly applied?

Accepted Answer

Combining multiple source records into a single target record using a function like SUM or COUNT

Answer

Filtering duplicate records

Answer

Splitting fields by delimiter

Answer

Reformatting date strings

Question 4

A canonical data model in enterprise integration is best described as:

Accepted Answer

A common, application-neutral data format used as an intermediary for message translation

Answer

A physical database schema shared across all applications

Answer

A data dictionary listing all field names in each system

Answer

A compressed binary format for high-throughput messaging

Question 5

Which data quality issue occurs when a field expected to hold a date contains a string like 'N/A'?

Accepted Answer

Data type mismatch

Answer

Schema drift

Answer

Referential integrity violation

Answer

Duplicate key error

Question 6

In ETL pipelines, what is the purpose of a surrogate key introduced during the transformation phase?

Accepted Answer

To provide a system-generated, unique identifier independent of source system keys

Answer

To encrypt the natural primary key from source systems

Answer

To concatenate composite keys into a single string

Answer

To replace NULL values in foreign key columns

Question 7

Which approach is used to handle schema evolution in data transformation pipelines with minimal disruption?

Accepted Answer

Using flexible schema registries and forward/backward-compatible serialization formats

Answer

Hard-coding field positions in every transform script

Answer

Stopping the pipeline and rewriting all mappings

Answer

Replacing the target system's schema to match the source