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Google GCP-DE Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Designing data processing systems | 20% | - Storage and data modeling
|
| Topic 2: Operationalizing data and ML pipelines | 30% | - Pipeline automation and orchestration
|
| Topic 3: Building and operationalizing data processing systems | 30% | - Data pipeline implementation
|
| Topic 4: Maintaining and optimizing data and ML solutions | 20% | - Machine learning integration
|
Google Data Engineer Sample Questions:
1. Each analytics team in your organization is running BigQuery jobs in their own projects. You want to enable each team to monitor slot usage within their projects. What should you do?
A) Create an aggregated log export at the organization level, capture the BigQuery job execution logs, create a custom metric based on the totalSlotMs, and create a Stackdriver Monitoring dashboard based on the custom metric
B) Create a Stackdriver Monitoring dashboard based on the BigQuery metric query/scanned_bytes
C) Create a log export for each project, capture the BigQuery job execution logs, create a custom metric based on the totalSlotMs, and create a Stackdriver Monitoring dashboard based on the custom metric
D) Create a Stackdriver Monitoring dashboard based on the BigQuery metric slots/allocated_for_project
2. 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 event time trigger
B) An hourly watermark
C) The with Allowed Lateness method
D) A processing time trigger
3. 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) For each Cloud Storage bucket or BigQuery dataset, decide which projects need acces
B) Find all the active members who have access to these projects, and create a Cloud IAM policy to grant access to all these users.
C) Create distinct groups for various teams, and specify groups in Cloud IAM policies.
D) Introduce resource hierarchy to leverage access control policy inheritance.
E) Only use service accounts when sharing data for Cloud Storage buckets and BigQuery datasets.
F) Use Cloud Deployment Manager to automate access provision.
4. Which of the following is NOT true about Dataflow pipelines?
A) Dataflow pipelines are tied to Dataflow, and cannot be run on any other runner
B) Dataflow pipelines can consume data from other Google Cloud services
C) Dataflow pipelines use a unified programming model, so can work both with streaming and batch data sources
D) Dataflow pipelines can be programmed in Java
5. Which of these is not a supported method of putting data into a partitioned table?
A) Create a partitioned table and stream new records to it every day.
B) Use ORDER BY to put a table's rows into chronological order and then change the table's type to "Partitioned".
C) If you have existing data in a separate file for each day, then create a partitioned table and upload each file into the appropriate partition.
D) Run a query to get the records for a specific day from an existing table and for the destination table, specify a partitioned table ending with the day in the format "$YYYYMMDD".
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: D | Question # 3 Answer: C,D | Question # 4 Answer: A | Question # 5 Answer: B |
