A financial trading platform processes real-time market data from Pub/Sub. They need to compute moving averages over 5-minute windows, but some events arrive up to 2 minutes late. They also need to ensure that the pipeline can handle a sudden spike in message volume without losing data. What should they do?

Use Dataflow with sliding windows of 5 minutes and no allowed lateness, relying on Pub/Sub's default retention.

Use Dataproc with Spark Streaming and a 5-minute batch interval, with no special handling for late data.

Use Dataflow with fixed windows of 5 minutes, allowed lateness of 2 minutes, and configure Pub/Sub to retain messages for at least 7 days.

Use Cloud Data Fusion with a 5-minute window and rely on its built-in late-data handling.

When integrating a new data source into an existing pipeline, which of the following is a key consideration?

The number of employees at the data source company

The color of the data source logo

The data source's marketing strategy

The schema of the new data source

A company uses Pub/Sub to ingest IoT sensor data. They have a Dataflow pipeline that aggregates data in 1-minute windows. Recently, they noticed that some data is missing from the output. They suspect that the Pub/Sub subscription is not delivering all messages. What should they do to diagnose and fix the issue?

Use a pull subscription instead of a push subscription.

Check the Pub/Sub subscription's unacked message count and the Dataflow pipeline's system lag, and increase the number of workers if needed.

Enable exactly-once delivery on the Pub/Sub subscription.

Increase the Pub/Sub message retention duration to ensure messages are not expired.

Which open-source technology is Cloud Data Fusion based on?

CDAP (Cask Data Application Platform)

Google CloudProfessional Data Engineer

Domain 2Objective 2

2.2 Building the Pipelines PROFESSIONAL-DATA-ENGINEER Practice Questions (Page 3)

Part of the Ingesting and processing the data domain, which accounts for ~25% of the PROFESSIONAL-DATA-ENGINEER exam. Google Cloud does not publish an official question count, but from its 120-minute exam (~50–80 total, ~13–20 in this domain), expect 4–7 from this objective — we provide 38 practice questions to prepare you well beyond it. (estimate)

38questions here

8free pages

10concepts

~25%of the exam

Questions 11–15

11expert · hard
A financial trading platform processes real-time market data from Pub/Sub. They need to compute moving averages over 5-minute windows, but some events arrive up to 2 minutes late. They also need to ensure that the pipeline can handle a sudden spike in message volume without losing data. What should they do?
Select an answer first
12foundation · easy
When integrating a new data source into an existing pipeline, which of the following is a key consideration?
Select an answer first
13expert · hard
A company uses Pub/Sub to ingest IoT sensor data. They have a Dataflow pipeline that aggregates data in 1-minute windows. Recently, they noticed that some data is missing from the output. They suspect that the Pub/Sub subscription is not delivering all messages. What should they do to diagnose and fix the issue?
Select an answer first
14foundation · easy
A data engineer notices that a column of customer ages contains the value -5 for several records. Which data cleansing technique is most appropriate to address this issue?
Select an answer first
15foundation · easy
Which open-source technology is Cloud Data Fusion based on?
Select an answer first

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2.2 Building the Pipelines PROFESSIONAL-DATA-ENGINEER Practice Questions (Page 3)

Questions 11–15

When integrating a new data source into an existing pipeline, which of the following is a key consideration?

A data engineer notices that a column of customer ages contains the value -5 for several records. Which data cleansing technique is most appropriate to address this issue?

Which open-source technology is Cloud Data Fusion based on?

Keep studying — Ingesting and processing the data