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Google GCP-DE Exam Syllabus Topics:

Google Data Engineer Sample Questions:

1. Which Google Cloud Platform service is an alternative to Hadoop with Hive?

A) BigQuery
B) Cloud Datastore
C) Cloud Bigtable
D) Cloud Dataflow

2. You are developing an application on Google Cloud that will automatically generate subject labels for users' blog posts. You are under competitive pressure to add this feature quickly, and you have no additional developer resources. No one on your team has experience with machine learning. What should you do?

A) Deploy the model using Cloud Machine Learning Engin
B) Call the Cloud Natural Language API from your applicatio
C) Call the Cloud Natural Language API from your applicatio
D) Call the model from your application and process the results as labels.
E) Process the generated Sentiment Analysis as labels.
F) Process the generated Entity Analysis as labels.
G) Deploy the model using a KubernetesEngine cluste
H) Build and train a text classification model using TensorFlo
I) Call the model from your application and process the results as labels.
J) Build and train a text classification model using TensorFlo

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

4. You work for a shipping company that uses handheld scanners to read shipping labels. Your company has strict data privacy standards that require scanners to only transmit recipients' personally identifiable information (PII) to analytics systems, which violates user privacy rules. You want to quickly build a scalable solution using cloud-native managed services to prevent exposure of PII to the analytics systems. What should you do?

A) Install a third-party data validation tool on Compute Engine virtual machines to check the incoming data for sensitive information.
B) Use the tagging and confidence levels to either pass or quarantine the data in a bucket for review.
C) Create an authorized view in BigQuery to restrict access to tables with sensitive data.
D) Build a Cloud Function that reads the topics and makes a call to the Cloud Data Loss Prevention AP
E) Use Stackdriver logging to analyze the data passed through the total pipeline to identify transactions that may contain sensitive information.

5. You are planning to migrate your current on-premises Apache Hadoop deployment to the cloud. You need to ensure that the deployment is as fault-tolerant and cost-effective as possible for long-running batch jobs. You want to use a managed service. What should you do?

A) Change references in scripts from hdfs:// to gs://
B) Install Hadoop and Spark on a 10-node Compute Engine instance group with preemptible instances.Store data in HDF
C) Store data in Cloud Storage, and change references in scripts from hdfs:// to gs://
D) Install the Cloud Storage connector, and store the data in Cloud Storag
E) Store data in Cloud Storage, and change references in scripts from hdfs:// to gs://
F) Use a standard persistent disk and 50% preemptible worker
G) Use an SSD persistent disk and 50% preemptible worker
H) Change references in scripts from hdfs:// to gs://
I) Deploy a Cloud Dataproc cluste
J) Install Hadoop and Spark on a 10-node Compute Engine instance group with standard instance
K) Deploy a Cloud Dataproc cluste

Solutions: