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Google GCP-DE Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Managing and optimizing solutions	20%-25%	- Reliability and scalability 1. Scale data workloads efficiently 2. Design highly available systems 3. Implement disaster recovery strategies - Managing resources and costs 1. Tune query and pipeline performance 2. Optimize storage and compute usage 3. Control operational costs
Topic 2: Designing data processing systems	22%-27%	- Designing data pipelines 1. Design orchestration workflows 2. Build ETL and ELT pipelines 3. Optimize pipeline performance and cost - Designing for data ingestion 1. Design batch and streaming ingestion solutions 2. Design scalable and reliable ingestion architecture 3. Select appropriate storage systems
Topic 3: Building and operationalizing data processing systems	28%-33%	- Operationalizing systems 1. Monitor data pipelines and workloads 2. Manage logging and alerting 3. Implement fault tolerance and recovery - Building data processing systems 1. Use BigQuery, Dataflow, Pub/Sub, Dataproc and related services 2. Implement batch processing systems 3. Implement streaming data systems
Topic 4: Ensuring solution quality	20%-25%	- Data quality management 1. Maintain metadata and lineage 2. Implement data governance 3. Validate and clean data - Security and compliance 1. Manage IAM and access control 2. Implement encryption and compliance controls 3. Protect sensitive data

Google Data Engineer Sample Questions:

1. When using Cloud Dataproc clusters, you can access the YARN web interface by configuring a browser to connect through a proxy.

A) HTTP
B) SOCKS
C) HTTPS
D) VPN

2. You are planning to use Google's Dataflow SDK to analyze customer data such as displayed below. Your project requirement is to extract only the customer name Passing Certification Exams Made Easy visit - https://www.2PassEasy.com from the data source and then write to an output PCollection.
Tom,555 X street Tim,553 Y street Sam, 111 Z street
Which operation is best suited for the above data processing requirement?

A) Data extraction
B) Source API
C) ParDo
D) Sink API

3. Which of these rules apply when you add preemptible workers to a Dataproc cluster (select 2 answers)?

A) Preemptible workers cannot use persistent disk.
B) A Dataproc cluster cannot have only preemptible workers.
C) If a preemptible worker is reclaimed, then a replacement worker must be added manually.
D) Preemptible workers cannot store data.

4. You are creating a new pipeline in Google Cloud to stream IoT data from Cloud Pub/Sub through Cloud Dataflow to BigQuery. While previewing the data, you notice that roughly 2% of the data appears to be corrupt. You need to modify the Cloud Dataflow pipeline to filter out this corrupt data. What should you do?

A) Add a Partition transform in Cloud Dataflow to separate valid data from corrupt data.
B) Add a SideInput that returns a Boolean if the element is corrupt.
C) Add a ParDo transform in Cloud Dataflow to discard corrupt elements.
D) Add a GroupByKey transform in Cloud Dataflow to group all of the valid data together and discard the rest.

5. You receive data files in CSV format monthly from a third party. You need to cleanse this data, but every third month the schema of the files changes. Your requirements for implementing these transformations include:
Executing the transformations on a schedule
Enabling non-developer analysts to modify transformations
Providing a graphical tool for designing transformations
What should you do?

A) Use Apache Spark on Cloud Dataproc to infer the schema of the CSV file before creating a Dataframe.Then implement the transformations in Spark SQL before writing the data out to Cloud Storage and loading into BigQuery
B) Merge the transformed tables together with a SQL query
C) Load each month's CSV data into BigQuery, and write a SQL query to transform the data to a standard scheme
D) Use Cloud Dataprep to build and maintain the transformation recipes, and execute them on a scheduled basis
E) Help the analysts write a Cloud Dataflow pipeline in Python to perform the transformatio
F) The Python code should be stored in a revision control system and modified as the incoming data's schema changes

Solutions:

Question # 1
Answer: B

Question # 2
Answer: C

Question # 3
Answer: B,D

Question # 4
Answer: C

Question # 5
Answer: E