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Google GCP-DE Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Building and operationalizing data processing systems | 30% | - Data pipeline implementation
|
| Operationalizing data and ML pipelines | 30% | - Pipeline automation and orchestration
|
| Maintaining and optimizing data and ML solutions | 20% | - Security and governance
|
| Designing data processing systems | 20% | - Data pipeline architecture design
|
Google Data Engineer Sample Questions:
You need to choose a database for a new project that has the following requirements:
Fully managed
Able to automatically scale up
Transactionally consistent
Able to scale up to 6 TB
Able to be queried using SQL Which database do you choose?
- A. Cloud Spanner
- B. Cloud Datastore
- C. Cloud SQL
- D. Cloud Bigtable
Correct Answer: A 🗳️
As your organization expands its usage of GCP, many teams have started to create their own projects. Projects are further multiplied to accommodate different stages of deployments and target audiences. Each project requires unique access control configurations. The central IT team needs to have access to all projects. Furthermore, data from Cloud Storage buckets and BigQuery datasets must be shared for use in other projects in an ad hoc way. You want to simplify access control management by minimizing the number of policies. Which two steps should you take? Choose 2 answers.
- A. Only use service accounts when sharing data for Cloud Storage buckets and BigQuery datasets.
- B. Use Cloud Deployment Manager to automate access provision.
- C. Create distinct groups for various teams, and specify groups in Cloud IAM policies.
- D. Find all the active members who have access to these projects, and create a Cloud IAM policy to grant access to all these users.
- E. Introduce resource hierarchy to leverage access control policy inheritance.
- F. For each Cloud Storage bucket or BigQuery dataset, decide which projects need acces
Correct Answer: C,E 🗳️
You used Cloud Dataprep to create a recipe on a sample of data in a BigQuery table. You want to reuse this recipe on a daily upload of data with the same schema, after the load job with variable execution time completes. What should you do?
- A. Create a cron schedule in Cloud Dataprep.
- B. Export the Cloud Dataprep job as a Cloud Dataflow template, and incorporate it into a Cloud Composer job.
- C. Create an App Engine cron job to schedule the execution of the Cloud Dataprep job.
- D. Export the recipe as a Cloud Dataprep template, and create a job in Cloud Scheduler.
Correct Answer: D 🗳️
Which Cloud Dataflow / Beam feature should you use to aggregate data in an unbounded data source every hour based on the time when the data entered the pipeline?
- A. An hourly watermark
- B. An event time trigger
- C. A processing time trigger
- D. The with Allowed Lateness method
Correct Answer: C 🗳️
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You operate an IoT pipeline built around Apache Kafka that normally receives around 5000 messages per second. You want to use Google Cloud Platform to create an alert as soon as the moving average over 1 hour drops below 4000 messages per second. What should you do?
- A. Use a Cloud Dataflow template to write your messages from Cloud Pub/Sub to Cloud Bigtabl
- B. Consume the stream of data in Cloud Dataflow using Kafka I
- C. Use Cloud Scheduler to run a script every hour that counts the number of rows created in Cloud Bigtable in the last hour
- D. If that number falls below 4000, send an alert.
- E. Set a fixed time window of 1 hour.Compute the average when the window closes, and send an alert if the average is less than 4000 messages.
- F. Use Kafka Connect to link your Kafka message queue to Cloud Pub/Su
- G. Compute the average when the window closes, and send an alert if the average is less than 4000 messages.
- H. Use Cloud Scheduler to run a script every five minutes that counts the number of rows created in BigQuery in the last hour
- I. Use a Cloud Dataflow template to write your messages from Cloud Pub/Sub to BigQuer
- J. Set a sliding time window of 1 hour every 5 minute
- K. If that number falls below 4000, send an alert.
- L. Use Kafka Connect to link your Kafka message queue to Cloud Pub/Su
- M. Consume the stream of data in Cloud Dataflow using Kafka I
Correct Answer: G 🗳️
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