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Google GCP-DE Exam Syllabus Topics:

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

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Google Data Engineer Sample Questions (Q41-Q46):

NEW QUESTION # 41
MJTelco needs you to create a schema in Google Bigtable that will allow for the historical analysis of the last 2 years of records. Each record that comes in is sent every 15 minutes, and contains a unique identifier of the device and a data record. The most common query is for all the data for a given device for a given day. Which schema should you use?

Answer: C


NEW QUESTION # 42
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?

Answer: A


NEW QUESTION # 43
You are designing storage for two relational tables that are part of a 10-TB database on Google Cloud. You want to support transactions that scale horizontally. You also want to optimize data for range queries on nonkey columns. What should you do?

Answer: C

Explanation:
Reference: https://cloud.google.com/solutions/data-lifecycle-cloud-platform


NEW QUESTION # 44
You are responsible for writing your company's ETL pipelines to run on an Apache Hadoop cluster. The pipeline will require some checkpointing and splitting pipelines. Which method should you use to write the pipelines?

Answer: D


NEW QUESTION # 45
For the best possible performance, what is the recommended zone for your Compute Engine instance and Cloud Bigtable instance?

Answer: D

Explanation:
It is recommended to create your Compute Engine instance in the same zone as your Cloud Bigtable instance for the best possible performance, If it's not possible to create a instance in the same zone, you should create your instance in another zone within the same region. For example, if your Cloud Bigtable instance is located in us-central1-b, you could create your instance in us-central1-f. This change may result in several milliseconds of additional latency for each Cloud Bigtable request.
It is recommended to avoid creating your Compute Engine instance in a different region from your Cloud Bigtable instance, which can add hundreds of milliseconds of latency to each Cloud Bigtable request.
Reference: https://cloud.google.com/bigtable/docs/creating-compute-instance


NEW QUESTION # 46
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