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Google Data Engineer Sample Questions:

1. You are planning to use Google's Dataflow SDK to analyze customer data such as displayed below. Your project requirement is to extract only the customer name Passing Certification Exams Made Easy visit - https://www.2PassEasy.com from the data source and then write to an output PCollection.
Tom,555 X street Tim,553 Y street Sam, 111 Z street
Which operation is best suited for the above data processing requirement?

A) Source API
B) Sink API
C) Data extraction
D) ParDo

2. You want to automate execution of a multi-step data pipeline running on Google Cloud. The pipeline includes Cloud Dataproc and Cloud Dataflow jobs that have multiple dependencies on each other. You want to use managed services where possible, and the pipeline will run every day. Which tool should you use?

A) Workflow Templates on Cloud Dataproc
B) Cloud Composer
C) cron
D) Cloud Scheduler

3. You are building a model to predict whether or not it will rain on a given day. You have thousands of input features and want to see if you can improve training speed by removing some features while having a minimum effect on model accuracy. What can you do?

A) Remove the features that have null values for more than 50% of the training records.
B) Eliminate features that are highly correlated to the output labels.
C) Instead of feeding in each feature individually, average their values in batches of 3.
D) Combine highly co-dependent features into one representative feature.

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) Introduce data compression for each file to increase the rate file of file transfer.
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) Transmit the TAR files instead, and disassemble the CSV files in the cloud upon receiving them.
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) Contact your internet service provider (ISP) to increase your maximum bandwidth to at least 100 Mbps.

5. 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

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