Google Data Engineer Sample Questions:

1. You are a retailer that wants to integrate your online sales capabilities with different in-home assistants, such as Google Home. You need to interpret customer voice commands and issue an order to the backend systems. Which solutions should you choose?

A) Dialogflow Enterprise Edition
B) Cloud Natural Language API
C) Cloud Speech-to-Text API
D) Cloud AutoML Natural Language

2. You need to choose a database for a new project that has the following requirements:
Fully managed
Able to automatically scale up
Transactionally consistent
Able to scale up to 6 TB
Able to be queried using SQL Which database do you choose?

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

3. You are building a new application that you need to collect data from in a scalable way. Data arrives continuously from the application throughout the day, and you expect to generate approximately 150 GB of JSON data per day by the end of the year. Your requirements are: Decoupling producer from consumer Space and cost-efficient storage of the raw ingested data, which is to be stored indefinitely Near real-time SQL query Maintain at least 2 years of historical data, which will be queried with SQ Which pipeline should you use to meet these requirements?

A) Write a tool to poll the API and write data to Cloud Storage as gzipped JSON files.
B) Create an application that publishes events to Cloud Pub/Sub, and create Spark jobs on Cloud Dataproc to convert the JSON data to Avro format, stored on HDFS on Persistent Disk.
C) Create an application that writes to a Cloud SQL database to store the dat
D) Create an application that publishes events to Cloud Pub/Sub, and create a Cloud Dataflow pipeline that transforms the JSON event payloads to Avro, writing the data to Cloud Storage and BigQuery.
E) Create an application that provides an AP
F) Set up periodic exports of the database to write to Cloud Storage and load into BigQuery.

4. You work for a large fast food restaurant chain with over 400,000 employees. You store employee information in Google BigQuery in a Users table consisting of a FirstName field and a LastName field. A member of IT is building an application and asks you to modify the schema and data in BigQuery so the application can query a FullName field consisting of the value of the FirstName field concatenated with a space, followed by the value of the LastName field for each employee. How can you make that data available while minimizing cost?

A) Create a view in BigQuery that concatenates the FirstName and LastName field values to produce the FullName.
B) Run an UPDATE statement that updates the FullName column for each user with the concatenation of the FirstName and LastName values.
C) Create a Google Cloud Dataflow job that queries BigQuery for the entire Users table, concatenates the FirstName value and LastName value for each user, and loads the proper values for FirstName, LastName, and FullName into a new table in BigQuery.
D) Add a new column called FullName to the Users tabl
E) Use BigQuery to export the data for the table to a CSV fil
F) Create a Google Cloud Dataproc job to process the CSV file and output a new CSV file containing the proper values for FirstName, LastName and FullNam G. Run a BigQuery load job to load the new CSV file into BigQuery.

5. Which of the following statements is NOT true regarding Bigtable access roles?

A) Using IAM roles, you cannot give a user access to only one table in a project, rather than all tables in a project.
B) To give a user access to only one table in a project, grant the user the Bigtable Editor role for that table.
C) To give a user access to only one table in a project, you must configure access through your application.
D) You can configure access control only at the project level.

Solutions: