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Google GCP-DE Exam Syllabus Topics:

Google Data Engineer Sample Questions:

1. You work for a global shipping company. You want to train a model on 40 TB of data to predict which ships in each geographic region are likely to cause delivery delays on any given day. The model will be based on multiple attributes collected from multiple sources. Telemetry data, including location in GeoJSON format, will be pulled from each ship and loaded every hour. You want to have a dashboard that shows how many and which ships are likely to cause delays within a region. You want to use a storage solution that has native functionality for prediction and geospatial processing. Which storage solution should you use?

A) Cloud Datastore
B) BigQuery
C) Cloud Bigtable
D) Cloud SQL for PostgreSQL

2. Your company maintains a hybrid deployment with GCP, where analytics are performed on your anonymized customer dat a. The data are imported to Cloud Storage from your data center through parallel uploads to a data transfer server running on GCP. Management informs you that the daily transfers take too long and have asked you to fix the problem. You want to maximize transfer speeds. Which action should you take?

A) Increase the size of the Google Persistent Disk on your server.
B) Increase your network bandwidth from Compute Engine to Cloud Storage.
C) Increase the CPU size on your server.
D) Increase your network bandwidth from your datacenter to GCP.

3. Suppose you have a table that includes a nested column called "city" inside a column called "person", but when you try to submit the following query in BigQuery, it gives you an error.
SELECT person FROM `project1.example.table1` WHERE city = "London"
How would you correct the error?

A) Add ", UNNEST(person)" before the WHERE clause.
B) Change "person" to "person.city".
C) Change "person" to "city.person".
D) Add ", UNNEST(city)" before the WHERE clause.

4. Cloud Dataproc is a managed Apache Hadoop and Apache service.

A) Ignite
B) Fire
C) Spark
D) Blaze

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 Bigtable
B) BigQuery and Cloud Storage
C) Cloud Datastore and Cloud Bigtable
D) Cloud Bigtable and Cloud SQL

Solutions: