What is the primary purpose of partitioning a Delta table?

To improve query performance by reducing the amount of data scanned

To increase the number of files in the table

An e-commerce company receives order data from multiple regional databases. They need to create a daily aggregated report of total sales by region. The data volume is moderate, and the report is not time-critical. Which data loading method should they use?

Batch ingestion using a scheduled notebook

Streaming ingestion with a sliding window

Incremental load using Change Data Capture

Real-time ingestion using Azure Event Hubs

A fact table stores sales transactions. Queries frequently filter by `order_date` and `store_id`. The table is partitioned by `order_date` (year/month/day). You notice that queries filtering only by `store_id` are slow. Which change would most improve performance for those queries?

Remove partitioning and use liquid clustering on `order_date` and `store_id`.

Create a view that filters by `store_id`.

Repartition the table by `store_id`.

Add Z-ordering on `store_id` within each partition.

A data engineering team has a Delta table that is frequently updated with new rows and occasionally updated existing rows. Queries often filter on a high-cardinality column, customer_id. The table is not partitioned. Which optimization should they apply to improve query performance?

Liquid clustering on customer_id

Microsoft Certified:Azure Databricks Data Engineer Associate

Domain 3Objective 1

Design and Implement Data Modeling in Unity Catalog DP-750 Practice Questions (Page 4)

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 16–20

16foundation · easy
What is the primary purpose of partitioning a Delta table?
Select an answer first
17application · medium
An e-commerce company receives order data from multiple regional databases. They need to create a daily aggregated report of total sales by region. The data volume is moderate, and the report is not time-critical. Which data loading method should they use?
Select an answer first
18foundation · easy
A data engineer needs to load a large historical dataset that is available as a one-time export. Which data loading method is most suitable?
Select an answer first
19application · medium
A fact table stores sales transactions. Queries frequently filter by `order_date` and `store_id`. The table is partitioned by `order_date` (year/month/day). You notice that queries filtering only by `store_id` are slow. Which change would most improve performance for those queries?
Select an answer first
20application · medium
A data engineering team has a Delta table that is frequently updated with new rows and occasionally updated existing rows. Queries often filter on a high-cardinality column, customer_id. The table is not partitioned. Which optimization should they apply to improve query performance?
Select an answer first

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