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Google GCP-DE Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Designing data processing systems22%-27%- Designing data pipelines
  • 1. Optimize pipeline performance and cost
  • 2. Design orchestration workflows
  • 3. Build ETL and ELT pipelines
- Designing for data ingestion
  • 1. Design scalable and reliable ingestion architecture
  • 2. Select appropriate storage systems
  • 3. Design batch and streaming ingestion solutions
Topic 2: Managing and optimizing solutions20%-25%- Managing resources and costs
  • 1. Control operational costs
  • 2. Tune query and pipeline performance
  • 3. Optimize storage and compute usage
- Reliability and scalability
  • 1. Scale data workloads efficiently
  • 2. Implement disaster recovery strategies
  • 3. Design highly available systems
Topic 3: Building and operationalizing data processing systems28%-33%- Building data processing systems
  • 1. Use BigQuery, Dataflow, Pub/Sub, Dataproc and related services
  • 2. Implement streaming data systems
  • 3. Implement batch processing systems
- Operationalizing systems
  • 1. Monitor data pipelines and workloads
  • 2. Implement fault tolerance and recovery
  • 3. Manage logging and alerting
Topic 4: Ensuring solution quality20%-25%- Data quality management
  • 1. Validate and clean data
  • 2. Implement data governance
  • 3. Maintain metadata and lineage
- Security and compliance
  • 1. Manage IAM and access control
  • 2. Protect sensitive data
  • 3. Implement encryption and compliance controls

Google Data Engineer Sample Questions:

1. What are two methods that can be used to denormalize tables in BigQuery?

A) 1) Use nested repeated fields; 2) Use a partitioned table
B) 1) Use a partitioned table; 2) Join tables into one table
C) 1) Split table into multiple tables; 2) Use a partitioned table
D) 1) Join tables into one table; 2) Use nested repeated fields


2. You are operating a Cloud Dataflow streaming pipeline. The pipeline aggregates events from a Cloud Pub/Sub subscription source, within a window, and sinks the resulting aggregation to a Cloud Storage bucket. The source has consistent throughput. You want to monitor an alert on behavior of the pipeline with Cloud Stackdriver to ensure that it is processing dat a. Which Stackdriver alerts should you create?

A) An alert based on an increase of instance/storage/used_bytes for the source and a rate of change decrease of subscription/num_undelivered_messages for the destination
B) An alert based on a decrease of instance/storage/used_bytes for the source and a rate of change increase of subscription/num_undelivered_messages for the destination
C) An alert based on a decrease of subscription/num_undelivered_messages for the source and a rate of change increase of instance/storage/used_bytes for the destination
D) An alert based on an increase of subscription/num_undelivered_messages for the source and a rate of change decrease of instance/storage/used_bytes for the destination


3. When a Cloud Bigtable node fails, is lost.

A) the last transaction
B) all data
C) the time dimension
D) no data


4. By default, which of the following windowing behavior does Dataflow apply to unbounded data sets?

A) Windows at every 10 minutes
B) Windows at every 1 minute
C) Single, Global Window
D) Windows at every 100 MB of data


5. What is the general recommendation when designing your row keys for a Cloud Bigtable schema?

A) Keep your row key reasonably short
B) Keep your row key as long as the field permits
C) Include multiple time series values within the row key
D) Keep the row keep as an 8 bit integer


Solutions:

Question # 1
Answer: D
Question # 2
Answer: D
Question # 3
Answer: D
Question # 4
Answer: C
Question # 5
Answer: A

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