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Google Professional-Data-Engineer Exam Sample Questions

Question # 1

Which of the following is not possible using primitive roles?

A. Give a user viewer access to BigQuery and owner access to Google Compute Engine instances.

B. Give UserA owner access and UserB editor access for all datasets in a project.

C. Give a user access to view all datasets in a project, but not run queries on them.

D. Give GroupA owner access and GroupB editor access for all datasets in a project.

Answer

C.

Give a user access to view all datasets in a project, but not run queries on them.

Primitive roles can be used to give owner, editor, or viewer access to a user or group, but they can't be used to
separate data access permissions from job-running permissions

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Question # 2

Your company is performing data preprocessing for a learning algorithm in Google Cloud Dataflow. Numerous data logs are being are being generated during this step, and the team wants to analyze them. Due to the dynamic nature of the campaign, the data is growing exponentially every hour. The data scientists have written the following code to read the data for a new key features in the logs. BigQueryIO.Read .named(“ReadLogData”) .from(“clouddataflow-readonly:samples.log_data”) You want to improve the performance of this data read. What should you do?

A. Specify the TableReference object in the code.

B. Use .fromQuery operation to read specific fields from the table.

C. Use of both the Google BigQuery TableSchema and TableFieldSchema classes.

D. Call a transform that returns TableRow objects, where each element in the PCollexction represents a single row in the table.

Answer

D.

Call a transform that returns TableRow objects, where each element in the PCollexction
represents a single row in the table.

---

Question # 3

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

A. 1) Split table into multiple tables; 2) Use a partitioned table

B. 1) Join tables into one table; 2) Use nested repeated fields

C. 1) Use a partitioned table; 2) Join tables into one table

D. 1) Use nested repeated fields; 2) Use a partitioned table

Answer

B.

1) Join tables into one table; 2) Use nested repeated fields

Explanation
The conventional method of denormalizing data involves simply writing a fact, along with all its dimensions,
into a flat table structure. For example, if you are dealing with sales transactions, you would write each
individual fact to a record, along with the accompanying dimensions such as order and customer information.
The other method for denormalizing data takes advantage of BigQuery’s native support for nested and
repeated structures in JSON or Avro input data. Expressing records using nested and repeated structures can
provide a more natural representation of the underlying data. In the case of the sales order, the outer part of a
JSON structure would contain the order and customer information, and the inner part of the structure would
contain the individual line items of the order, which would be represented as nested, repeated elements.

---

Question # 4

What are all of the BigQuery operations that Google charges for?

A. Storage, queries, and streaming inserts

B. Storage, queries, and loading data from a file

C. Storage, queries, and exporting data

D. Queries and streaming inserts

Answer

A.

Storage, queries, and streaming inserts

Explanation
Google charges for storage, queries, and streaming inserts. Loading data from a file and exporting data are free
operations.

---

Question # 5

Your company uses a proprietary system to send inventory data every 6 hours to a data ingestion service in the cloud. Transmitted data includes a payload of several fields and the timestamp of the transmission. If there are any concerns about a transmission, the system re-transmits the data. How should you deduplicate the data most efficiency?

A. Assign global unique identifiers (GUID) to each data entry.

B. Compute the hash value of each data entry, and compare it with all historical data.

C. Store each data entry as the primary key in a separate database and apply an index.

D. Maintain a database table to store the hash value and other metadata for each data entry.

Answer

D.

Maintain a database table to store the hash value and other metadata for each data
entry.

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