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Google GCP-DE Exam Syllabus Topics:

Google Data Engineer Sample Questions:

Question 1

Flowlogistic's CEO wants to gain rapid insight into their customer base so his sales team can be better informed in the field. This team is not very technical, so they've purchased a visualization tool to simplify the creation of BigQuery reports. However, they've been overwhelmed by all the data in the table, and are spending a lot of money on queries trying to find the data they need. You want to solve their problem in the most cost-effective way. What should you do?

A. Create an additional table with only the necessary columns.
B. Export the data into a Google Sheet for virtualization.
C. Create a view on the table to present to the virtualization tool.
D. Create identity and access management (IAM) roles on the appropriate columns, so only they appear in a query.

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

Question 3

Each analytics team in your organization is running BigQuery jobs in their own projects. You want to enable each team to monitor slot usage within their projects. What should you do?

A. Create a Stackdriver Monitoring dashboard based on the BigQuery metric slots/allocated_for_project
B. Create an aggregated log export at the organization level, capture the BigQuery job execution logs, create a custom metric based on the totalSlotMs, and create a Stackdriver Monitoring dashboard based on the custom metric
C. Create a log export for each project, capture the BigQuery job execution logs, create a custom metric based on the totalSlotMs, and create a Stackdriver Monitoring dashboard based on the custom metric
D. Create a Stackdriver Monitoring dashboard based on the BigQuery metric query/scanned_bytes

Question 4

You are building a new application that you need to collect data from in a scalable way. Data arrives continuously from the application throughout the day, and you expect to generate approximately 150 GB of JSON data per day by the end of the year. Your requirements are: Decoupling producer from consumer Space and cost-efficient storage of the raw ingested data, which is to be stored indefinitely Near real-time SQL query Maintain at least 2 years of historical data, which will be queried with SQ Which pipeline should you use to meet these requirements?

A. Create an application that publishes events to Cloud Pub/Sub, and create a Cloud Dataflow pipeline that transforms the JSON event payloads to Avro, writing the data to Cloud Storage and BigQuery.
B. Create an application that publishes events to Cloud Pub/Sub, and create Spark jobs on Cloud Dataproc to convert the JSON data to Avro format, stored on HDFS on Persistent Disk.
C. Write a tool to poll the API and write data to Cloud Storage as gzipped JSON files.
D. Create an application that writes to a Cloud SQL database to store the dat
E. Create an application that provides an AP
F. Set up periodic exports of the database to write to Cloud Storage and load into BigQuery.

Question 5

MJTelco is building a custom interface to share dat
a. They have these requirements:
They need to do aggregations over their petabyte-scale datasets.
They need to scan specific time range rows with a very fast response time (milliseconds). Which combination of Google Cloud Platform products should you recommend?

A. BigQuery and Cloud Storage
B. Cloud Datastore and Cloud Bigtable
C. BigQuery and Cloud Bigtable
D. Cloud Bigtable and Cloud SQL

Solutions: