PCDE Migrate data solutions Practice Question
A company wants to migrate a 10 TB Redshift data warehouse to BigQuery with minimal downtime. Which combination of services should they use?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Use BigQuery Data Transfer Service for Redshift for initial and incremental loads.
BigQuery Data Transfer Service can directly load data from Redshift. Schema Conversion Tool (SCTS) helps convert DDL. For minimal downtime, an initial load plus CDC or incremental loads can be used.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Use BigQuery Data Transfer Service for Redshift for initial and incremental loads.
Why this is correct
BQ DTS supports Redshift as a source, enabling both initial and scheduled incremental loads.
- ✗
Use DMS with a Redshift source endpoint.
Why it's wrong here
DMS does not support Redshift as a source database.
- ✗
Export Redshift data to CSV and load using bq load.
Why it's wrong here
This works but is not optimal for minimal downtime; incremental loads are manual.
- ✗
Use Cloud Dataflow to stream from Redshift to BigQuery.
Why it's wrong here
Cloud Dataflow is a stream-processing service, not a batch-export tool; Redshift lacks a native streaming CDC connector to Dataflow, so this approach cannot perform the initial 10 TB bulk load without a separate export mechanism like UNLOAD to Amazon S3. It is tempting because Dataflow excels at real-time ingestion for ongoing updates, making it the correct choice for continuous synchronisation after an initial snapshot migration.
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