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Google Data Engineer Sample Questions:

1. MJTelco needs you to create a schema in Google Bigtable that will allow for the historical analysis of the last 2 years of records. Each record that comes in is sent every 15 minutes, and contains a unique identifier of the device and a data record. The most common query is for all the data for a given device for a given day. Which schema should you use?

A) Rowkey: device_idColumn data: date, data_point
B) Rowkey: date#device_idColumn data: data_point
C) Rowkey: dateColumn data: device_id, data_point
D) Rowkey: data_pointColumn data: device_id, date
E) Rowkey: date#data_pointColumn data: device_id

2. You want to process payment transactions in a point-of-sale application that will run on Google Cloud Platform. Your user base could grow exponentially, but you do not want to manage infrastructure scaling.
Which Google database service should you use?

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

3. You are running a pipeline in Cloud Dataflow that receives messages from a Cloud Pub/Sub topic and writes the results to a BigQuery dataset in the EU. Currently, your pipeline is located in europe-west4 and has a maximum of 3 workers, instance type n1-standard-1. You notice that during peak periods, your pipeline is struggling to process records in a timely fashion, when all 3 workers are at maximum CPU utilization. Which two actions can you take to increase performance of your pipeline? (Choose two.)

A) Create a new step in your pipeline to write to this table first, and then create a new pipeline to write from Cloud Bigtable to BigQuery
B) Create a temporary table in Cloud Spanner that will act as a buffer for new data
C) Increase the number of max workers
D) Create a new step in your pipeline to write to this table first, and then create a new pipeline to write from Cloud Spanner to BigQuery
E) Create a temporary table in Cloud Bigtable that will act as a buffer for new data
F) Use a larger instance type for your Cloud Dataflow workers
G) Change the zone of your Cloud Dataflow pipeline to run in us-central1

4. When a Cloud Bigtable node fails, is lost.

A) the last transaction
B) all data
C) no data
D) the time dimension

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 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
B) 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
C) Create a Stackdriver Monitoring dashboard based on the BigQuery metric query/scanned_bytes
D) Create a Stackdriver Monitoring dashboard based on the BigQuery metric slots/allocated_for_project

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