A dimensions table stores product information. The `price` attribute changes infrequently. The reporting team needs to see the current price and also the previous price for comparison. They do not need full history. Which SCD type should you implement?

Type 1 SCD that overwrites the price

Type 4 SCD with a separate history table

Type 2 SCD with `valid_from` and `valid_to` columns

Type 3 SCD with `current_price` and `previous_price` columns

A company stores raw application logs in JSON format in Azure Blob Storage. They need to ingest these logs into a Delta table for analysis. The logs are appended continuously, and the team wants to process them in near real-time. Which ingestion logic should they use?

Use a scheduled batch job to load all JSON files daily

Use Auto Loader with file notification to incrementally process new JSON files

Use Azure Data Factory to copy JSON files on a schedule

Use a notebook to manually load JSON files

A logistics company receives shipment status updates as JSON messages from IoT devices every few seconds. They need to ingest these messages into a Delta table for real-time tracking dashboards. The team also wants to handle late-arriving events without reprocessing the entire stream. Which ingestion approach should they use?

Use Structured Streaming in a notebook to read from the IoT hub and write to a Delta table

Use Lakeflow Connect to synchronize the IoT hub data into a Delta table

Batch load JSON files from a landing zone every hour

Use Azure Data Factory to copy JSON files into a Delta table on a schedule

What does granularity refer to in data modeling?

The number of columns in the table

The level of detail stored in a table

The data type of the primary key

The number of rows in the table

A large Delta table is used for both point queries on a high-cardinality column (device_id) and range queries on a low-cardinality column (event_date). The table receives frequent updates and inserts. The team has tried partitioning by event_date and Z-ordering on device_id, but query performance is still inconsistent. What should they do to improve performance with minimal manual maintenance?

Use deletion vectors to speed up point queries

Increase the number of partitions by adding a partition on device_id

Switch to liquid clustering on device_id and event_date

Run OPTIMIZE with Z-ordering more frequently

Microsoft Certified:Azure Databricks Data Engineer Associate

Domain 3Objective 1

Design and Implement Data Modeling in Unity Catalog DP-750 Practice Questions (Page 5)

Part of the Prepare and process data domain, which accounts for 30–35% of the DP-750 exam. Microsoft does not publish an official question count, but from its 120-minute exam (~50–80 total, ~15–28 in this domain), expect 4–7 from this objective — we provide 42 practice questions to prepare you well beyond it. (estimate)

42questions here

9free pages

10concepts

30–35%of the exam

Questions 21–25

21application · medium
A dimensions table stores product information. The `price` attribute changes infrequently. The reporting team needs to see the current price and also the previous price for comparison. They do not need full history. Which SCD type should you implement?
Select an answer first
22application · medium
A company stores raw application logs in JSON format in Azure Blob Storage. They need to ingest these logs into a Delta table for analysis. The logs are appended continuously, and the team wants to process them in near real-time. Which ingestion logic should they use?
Select an answer first
23application · medium
A logistics company receives shipment status updates as JSON messages from IoT devices every few seconds. They need to ingest these messages into a Delta table for real-time tracking dashboards. The team also wants to handle late-arriving events without reprocessing the entire stream. Which ingestion approach should they use?
Select an answer first
24foundation · easy
What does granularity refer to in data modeling?
Select an answer first
25expert · hard
A large Delta table is used for both point queries on a high-cardinality column (device_id) and range queries on a low-cardinality column (event_date). The table receives frequent updates and inserts. The team has tried partitioning by event_date and Z-ordering on device_id, but query performance is still inconsistent. What should they do to improve performance with minimal manual maintenance?
Select an answer first

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Design and Implement Data Modeling in Unity Catalog DP-750 Practice Questions (Page 5)

Questions 21–25

A dimensions table stores product information. The `price` attribute changes infrequently. The reporting team needs to see the current price and also the previous price for comparison. They do not need full history. Which SCD type should you implement?

A company stores raw application logs in JSON format in Azure Blob Storage. They need to ingest these logs into a Delta table for analysis. The logs are appended continuously, and the team wants to process them in near real-time. Which ingestion logic should they use?

What does granularity refer to in data modeling?

Keep studying — Prepare and process data