5.3.2. Data Ingestion Questions
Question 4
A retail company needs to track customer address changes over time for historical sales analysis by region. When a customer moves, the system should preserve the old address record and create a new one.
Which SCD type should you implement?
- A. Type 0
- B. Type 1
- C. Type 2
- D. Type 3
Answer: C. Type 2
Explanation: Type 2 SCD preserves complete history by adding new rows when values change. This enables historical analysis showing which region a customer was in at the time of each purchase. Type 1 would overwrite history (inappropriate for historical analysis), Type 0 never updates, and Type 3 only keeps current and previous values.
Question 5
You need to replicate data from Azure Cosmos DB and Azure Databricks Unity Catalog into Microsoft Fabric. Which mirroring approach should you use for each?
- A. Database mirroring for both
- B. Metadata mirroring for both
- C. Database mirroring for Cosmos DB, Metadata mirroring for Databricks
- D. Metadata mirroring for Cosmos DB, Database mirroring for Databricks
Answer: C. Database mirroring for Cosmos DB, Metadata mirroring for Databricks
Explanation: Azure Cosmos DB uses database mirroring, which replicates actual data using CDC. Azure Databricks uses metadata mirroring, which only replicates Unity Catalog information—the data stays in Databricks storage.
Question 6
You need to load 50 Parquet files into a Fabric Data Warehouse table. The files are located in Azure Blob Storage with names following the pattern sales_*.parquet.
What should you use?
- A. Individual INSERT statements for each file
- B. COPY INTO statement with wildcard
- C. Dataflow Gen2 for each file
- D. Create a shortcut to the files
Answer: B. COPY INTO statement with wildcard
Explanation: The COPY INTO statement supports wildcards for loading multiple files efficiently in a single operation. Individual INSERT statements would be extremely slow and resource-intensive. Dataflows for each file would be inefficient. Shortcuts provide access but don't load data into tables.