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Google GCP-DE Exam Syllabus Topics:

Google Data Engineer Sample Questions:

1. Which of the following is NOT true about Dataflow pipelines?

A) Dataflow pipelines use a unified programming model, so can work both with streaming and batch data sources
B) Dataflow pipelines can consume data from other Google Cloud services
C) Dataflow pipelines can be programmed in Java
D) Dataflow pipelines are tied to Dataflow, and cannot be run on any other runner

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

3. Which Cloud Dataflow / Beam feature should you use to aggregate data in an unbounded data source every hour based on the time when the data entered the pipeline?

A) An hourly watermark
B) A processing time trigger
C) The with Allowed Lateness method
D) An event time trigger

4. 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 your datacenter to GCP.
C) Increase the CPU size on your server.
D) Increase your network bandwidth from Compute Engine to Cloud Storage.

5. Your company produces 20,000 files every hour. Each data file is formatted as a comma separated values (CSV) file that is less than 4 KB. All files must be ingested on Google Cloud Platform before they can be processed. Your company site has a 200 ms latency to Google Cloud, and your Internet connection bandwidth is limited as 50 Mbps. You currently deploy a secure FTP (SFTP) server on a virtual machine in Google Compute Engine as the data ingestion point. A local SFTP client runs on a dedicated machine to transmit the CSV files as is. The goal is to make reports with data from the previous day available to the executives by 10:00 a.m. each day. This design is barely able to keep up with the current volume, even though the bandwidth utilization is rather low.
You are told that due to seasonality, your company expects the number of files to double for the next three months. Which two actions should you take? (choose two.)

A) Transmit the TAR files instead, and disassemble the CSV files in the cloud upon receiving them.
B) Redesign the data ingestion process to use gsutil tool to send the CSV files to a storage bucket in parallel.
C) Assemble 1,000 files into a tape archive (TAR) fil
D) Contact your internet service provider (ISP) to increase your maximum bandwidth to at least 100 Mbps.
E) Create an S3-compatible storage endpoint in your network, and use Google Cloud Storage Transfer Service to transfer on-premices data to the designated storage bucket.
F) Introduce data compression for each file to increase the rate file of file transfer.

Solutions: