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Google GCP-DE Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Managing and optimizing solutions | 20%-25% | - Managing resources and costs
|
| Ensuring solution quality | 20%-25% | - Data quality management
|
| Designing data processing systems | 22%-27% | - Designing data pipelines
|
| Building and operationalizing data processing systems | 28%-33% | - Operationalizing systems
|
Google Data Engineer Sample Questions:
1. Which of these rules apply when you add preemptible workers to a Dataproc cluster (select 2 answers)?
A) If a preemptible worker is reclaimed, then a replacement worker must be added manually.
B) A Dataproc cluster cannot have only preemptible workers.
C) Preemptible workers cannot store data.
D) Preemptible workers cannot use persistent disk.
2. 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?
A) Java using MapReduce
B) HiveQL using Hive
C) PigLatin using Pig
D) Python using MapReduce
3. You need to create a data pipeline that copies time-series transaction data so that it can be queried from within BigQuery by your data science team for analysis. Every hour, thousands of transactions are updated with a new status. The size of the intitial dataset is 1.5 PB, and it will grow by 3 TB per day. The data is heavily structured, and your data science team will build machine learning models based on this dat a. You want to maximize performance and usability for your data science team. Which two strategies should you adopt? Choose 2 answers.
A) Denormalize the data as must as possible.
B) Use BigQuery UPDATE to further reduce the size of the dataset.
C) Develop a data pipeline where status updates are appended to BigQuery instead of updated.
D) Copy a daily snapshot of transaction data to Cloud Storage and store it as an Avro fil
E) Preserve the structure of the data as much as possible.
F) Use BigQuery'ssupport for external data sources to query.
4. Which is not a valid reason for poor Cloud Bigtable performance?
A) The table's schema is not designed correctly.
B) The Cloud Bigtable cluster has too many nodes.
C) The workload isn't appropriate for Cloud Bigtable.
D) There are issues with the network connection.
5. You are a retailer that wants to integrate your online sales capabilities with different in-home assistants, such as Google Home. You need to interpret customer voice commands and issue an order to the backend systems. Which solutions should you choose?
A) Cloud Speech-to-Text API
B) Dialogflow Enterprise Edition
C) Cloud Natural Language API
D) Cloud AutoML Natural Language
Solutions:
| Question # 1 Answer: B,C | Question # 2 Answer: D | Question # 3 Answer: C,D | Question # 4 Answer: B | Question # 5 Answer: D |
