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Google GCP-DE Exam Syllabus Topics:

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

Google Data Engineer Sample Questions:

Question 1

You are integrating one of your internal IT applications and Google BigQuery, so users can query BigQuery from the application's interface. You do not want individual users to authenticate to BigQuery and you do not want to give them access to the dataset. You need to securely access BigQuery from your IT application.
What should you do?

A. Store the username and password for that user in a file on the files system, and use those credentials to access the BigQuery dataset
B. Create a dummy user and grant dataset access to that use
C. Create groups for your users and give those groups access to the dataset
D. Use the service account's private key to access the dataset
E. Integrate with a single sign-on (SSO) platform, and pass each user's credentials along with the query request
F. Create a service account and grant dataset access to that accoun


Question 2

You need to deploy additional dependencies to all of a Cloud Dataproc cluster at startup using an existing initialization action. Company security policies require that Cloud Dataproc nodes do not have access to the Internet so public initialization actions cannot fetch resources. What should you do?

A. Copy all dependencies to a Cloud Storage bucket within your VPC security perimeter
B. Use an SSH tunnel to give the Cloud Dataproc cluster access to the Internet
C. Use Resource Manager to add the service account used by the Cloud Dataproc cluster to the Network User role
D. Deploy the Cloud SQL Proxy on the Cloud Dataproc master


Question 3

An online retailer has built their current application on Google App Engine. A new initiative at the company mandates that they extend their application to allow their customers to transact directly via the application.
They need to manage their shopping transactions and analyze combined data from multiple datasets using a business intelligence (BI) tool. They want to use only a single database for this purpose. Which Google Cloud database should they choose?

A. Cloud BigTable
B. BigQuery
C. Cloud SQL
D. Cloud Datastore


Question 4

You are running a pipeline in Cloud Dataflow that receives messages from a Cloud Pub/Sub topic and writes the results to a BigQuery dataset in the EU. Currently, your pipeline is located in europe-west4 and has a maximum of 3 workers, instance type n1-standard-1. You notice that during peak periods, your pipeline is struggling to process records in a timely fashion, when all 3 workers are at maximum CPU utilization. Which two actions can you take to increase performance of your pipeline? (Choose two.)

A. Create a temporary table in Cloud Bigtable that will act as a buffer for new data
B. Create a temporary table in Cloud Spanner that will act as a buffer for new data
C. Change the zone of your Cloud Dataflow pipeline to run in us-central1
D. Create a new step in your pipeline to write to this table first, and then create a new pipeline to write from Cloud Spanner to BigQuery
E. Increase the number of max workers
F. Create a new step in your pipeline to write to this table first, and then create a new pipeline to write from Cloud Bigtable to BigQuery
G. Use a larger instance type for your Cloud Dataflow workers


Question 5

You have a data pipeline with a Cloud Dataflow job that aggregates and writes time series metrics to Cloud Bigtable. This data feeds a dashboard used by thousands of users across the organization. You need to support additional concurrent users and reduce the amount of time required to write the dat a. Which two actions should you take? (Choose two.)

A. Configure your Cloud Dataflow pipeline to use local execution
B. Increase the number of nodes in the Cloud Bigtable cluster
C. Modify your Cloud Dataflow pipeline to use the CoGroupByKey transform before writing to Cloud Bigtable
D. Modify your Cloud Dataflow pipeline to use the Flatten transform before writing to Cloud Bigtable
E. Increase the maximum number of Cloud Dataflow workers by setting maxNumWorkers in PipelineOptions


Solutions:

Question 1
Answer: F
Question 2
Answer: C
Question 3
Answer: A
Question 4
Answer: F,G
Question 5
Answer: C,D

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