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Google GCP-DE Exam Syllabus Topics:

Google Data Engineer Sample Questions:

1. 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) The with Allowed Lateness method
C) A processing time trigger
D) An event time trigger

2. What are two methods that can be used to denormalize tables in BigQuery?

A) 1) Use a partitioned table; 2) Join tables into one table
B) 1) Split table into multiple tables; 2) Use a partitioned table
C) 1) Join tables into one table; 2) Use nested repeated fields
D) 1) Use nested repeated fields; 2) Use a partitioned table

3. You have developed three data processing jobs. One executes a Cloud Dataflow pipeline that transforms data uploaded to Cloud Storage and writes results to BigQuery. The second ingests data from on-premises servers and uploads it to Cloud Storage. The third is a Cloud Dataflow pipeline that gets information from third-party data providers and uploads the information to Cloud Storage. You need to be able to schedule and monitor the execution of these three workflows and manually execute them when needed. What should you do?

A) Set up cron jobs in a Compute Engine instance to schedule and monitor the pipelines using GCP API calls.
B) Create a Direct Acyclic Graph in Cloud Composer to schedule and monitor the jobs.
C) Develop an App Engine application to schedule and request the status of the jobs using GCP API calls.
D) Use Stackdriver Monitoring and set up an alert with a Webhook notification to trigger the jobs.

4. 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) Assemble 1,000 files into a tape archive (TAR) fil
B) Redesign the data ingestion process to use gsutil tool to send the CSV files to a storage bucket in parallel.
C) Contact your internet service provider (ISP) to increase your maximum bandwidth to at least 100 Mbps.
D) Transmit the TAR files instead, and disassemble the CSV files in the cloud upon receiving them.
E) Introduce data compression for each file to increase the rate file of file transfer.
F) 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.

5. 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 be programmed in Java
C) Dataflow pipelines can consume data from other Google Cloud services
D) Dataflow pipelines are tied to Dataflow, and cannot be run on any other runner

Solutions: