A data engineer needs to build a pipeline that ingests both batch and streaming data into the same Unity Catalog table. The batch data arrives daily, and the streaming data arrives continuously. The engineer wants to use a notebook. Which approach should they use?

Use `foreachBatch` for both batch and streaming data

Use a batch write for the daily data and a streaming write with `outputMode("append")` for the streaming data, both targeting the same Delta table

Use SQL COPY INTO for the batch data and a streaming write for the streaming data

Use a streaming write for both batch and streaming data, treating the daily batch as a streaming source

A data engineering team wants to build a batch ingestion pipeline that uses Auto Loader to incrementally process new JSON files from a cloud storage location into a Unity Catalog table. They want to define the pipeline declaratively as code and manage it through the Databricks CLI. Which approach should they use?

Write a notebook with Auto Loader and schedule it as a job

Use Lakeflow Connect batch ingestion with a JSON source

Create a Lakeflow Spark Declarative Pipeline with Auto Loader as the source and a Delta table as the target

Use SQL COPY INTO in a notebook

After reading batch data into a DataFrame in a notebook, which method writes the data to a new table in Unity Catalog?

df.write.saveAsTable("catalog.schema.table")

df.save("catalog.schema.table")

df.writeStream.start("catalog.schema.table")

What is required to connect Databricks to Azure Event Hubs for streaming ingestion?

Event Hubs connection string and event hub name

An Azure Data Lake Storage account

Microsoft Certified:Azure Databricks Data Engineer Associate

Domain 3Objective 2

Ingest Data into 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 44 practice questions to prepare you well beyond it. (estimate)

44questions here

9free pages

11concepts

30–35%of the exam

Questions 16–20

16expert · hard
A data engineer needs to build a pipeline that ingests both batch and streaming data into the same Unity Catalog table. The batch data arrives daily, and the streaming data arrives continuously. The engineer wants to use a notebook. Which approach should they use?
Select an answer first
17foundation · easy
What does COPY INTO use to avoid reprocessing files that have already been loaded?
Select an answer first
18application · medium
A data engineering team wants to build a batch ingestion pipeline that uses Auto Loader to incrementally process new JSON files from a cloud storage location into a Unity Catalog table. They want to define the pipeline declaratively as code and manage it through the Databricks CLI. Which approach should they use?
Select an answer first
19foundation · easy
After reading batch data into a DataFrame in a notebook, which method writes the data to a new table in Unity Catalog?
Select an answer first
20foundation · easy
What is required to connect Databricks to Azure Event Hubs for streaming ingestion?
Select an answer first

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Ingest Data into Unity Catalog DP-750 Practice Questions (Page 4)

Questions 16–20

A data engineer needs to build a pipeline that ingests both batch and streaming data into the same Unity Catalog table. The batch data arrives daily, and the streaming data arrives continuously. The engineer wants to use a notebook. Which approach should they use?

What does COPY INTO use to avoid reprocessing files that have already been loaded?

After reading batch data into a DataFrame in a notebook, which method writes the data to a new table in Unity Catalog?

What is required to connect Databricks to Azure Event Hubs for streaming ingestion?

Keep studying — Prepare and process data