A logistics company needs to build a pipeline that ingests GPS data from IoT devices, validates it, and stores it in BigQuery. The data arrives in near real-time and they need to process it with low latency. They want to use a serverless solution. Which combination of products should they use?

Cloud Scheduler, Dataflow, and BigQuery

Cloud Pub/Sub, Dataflow, and BigQuery

Cloud Storage, Dataproc, and BigQuery

Cloud Pub/Sub, Cloud Functions, and BigQuery

A marketing analytics team needs to build a pipeline that ingests clickstream data from Cloud Storage, cleans it using Python, and loads it into BigQuery for analysis. They want to schedule this pipeline to run hourly and need minimal infrastructure management. Which combination of products should they use?

Cloud Composer, Dataproc, and BigQuery

Cloud Composer, Dataflow, and BigQuery

Cloud Scheduler, Cloud Functions, and BigQuery

Cloud Scheduler, Dataflow, and Cloud Storage

Google CloudAssociate Data Practitioner

Domain 3Objective 1

3.1 Design and Implement Simple Data Pipelines ASSOCIATE-DATA-PRACTITIONER Practice Questions (Page 2)

Part of the Data Pipeline Orchestration domain, which accounts for ~18% of the ASSOCIATE-DATA-PRACTITIONER exam.

12questions here

3free pages

3concepts

~18%of the exam

Questions 6–10

6foundation · easy
A team of data analysts with no programming experience needs to build a data transformation pipeline using a visual, drag-and-drop interface. They want to minimize the need for custom code. Which Google Cloud service is designed for this use case?
Select an answer first
7application · medium
A logistics company needs to build a pipeline that ingests GPS data from IoT devices, validates it, and stores it in BigQuery. The data arrives in near real-time and they need to process it with low latency. They want to use a serverless solution. Which combination of products should they use?
Select an answer first
8foundation · easy
A company needs to load raw, unprocessed data into a cloud data warehouse where the warehouse engine will perform the transformations. This approach is known as:
Select an answer first
9application · medium
A marketing analytics team needs to build a pipeline that ingests clickstream data from Cloud Storage, cleans it using Python, and loads it into BigQuery for analysis. They want to schedule this pipeline to run hourly and need minimal infrastructure management. Which combination of products should they use?
Select an answer first
10foundation · easy
A data engineering team needs to run a one-time, large-scale data transformation job on an existing Hadoop cluster. The team is most comfortable with Java and Spark. Which Google Cloud service is the most appropriate choice for this task?
Select an answer first

Finished these 5 questions?

Review the revealed explanations, or continue through the curriculum.

Next 5 questions →Back to ASSOCIATE-DATA-PRACTITIONER

Free Basic Practice is a study aid with revealable answers — not a scored exam. Examers.io is independent and not affiliated with or endorsed by Google Cloud. “ASSOCIATE-DATA-PRACTITIONER” is a trademark of its owner, used for identification only.

3.1 Design and Implement Simple Data Pipelines ASSOCIATE-DATA-PRACTITIONER Practice Questions (Page 2)

Questions 6–10

A team of data analysts with no programming experience needs to build a data transformation pipeline using a visual, drag-and-drop interface. They want to minimize the need for custom code. Which Google Cloud service is designed for this use case?

A logistics company needs to build a pipeline that ingests GPS data from IoT devices, validates it, and stores it in BigQuery. The data arrives in near real-time and they need to process it with low latency. They want to use a serverless solution. Which combination of products should they use?

A company needs to load raw, unprocessed data into a cloud data warehouse where the warehouse engine will perform the transformations. This approach is known as:

A data engineering team needs to run a one-time, large-scale data transformation job on an existing Hadoop cluster. The team is most comfortable with Java and Spark. Which Google Cloud service is the most appropriate choice for this task?

Keep studying — Data Pipeline Orchestration