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Professional-Data-Engineer Practice Exam Questions and Answers

Google Professional Data Engineer Exam

Last Update 1 day ago
Total Questions : 383

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Question # 1

Flowlogistic is rolling out their real-time inventory tracking system. The tracking devices will all send package-tracking messages, which will now go to a single Google Cloud Pub/Sub topic instead of the Apache Kafka cluster. A subscriber application will then process the messages for real-time reporting and store them in Google BigQuery for historical analysis. You want to ensure the package data can be analyzed over time.

Which approach should you take?

Options:

A.  

Attach the timestamp on each message in the Cloud Pub/Sub subscriber application as they are received.

B.  

Attach the timestamp and Package ID on the outbound message from each publisher device as they are sent to Clod Pub/Sub.

C.  

Use the NOW () function in BigQuery to record the event’s time.

D.  

Use the automatically generated timestamp from Cloud Pub/Sub to order the data.

Discussion 0
Question # 2

Flowlogistic wants to use Google BigQuery as their primary analysis system, but they still have Apache Hadoop and Spark workloads that they cannot move to BigQuery. Flowlogistic does not know how to store the data that is common to both workloads. What should they do?

Options:

A.  

Store the common data in BigQuery as partitioned tables.

B.  

Store the common data in BigQuery and expose authorized views.

C.  

Store the common data encoded as Avro in Google Cloud Storage.

D.  

Store he common data in the HDFS storage for a Google Cloud Dataproc cluster.

Discussion 0
Question # 3

Flowlogistic’s management has determined that the current Apache Kafka servers cannot handle the data volume for their real-time inventory tracking system. You need to build a new system on Google Cloud Platform (GCP) that will feed the proprietary tracking software. The system must be able to ingest data from a variety of global sources, process and query in real-time, and store the data reliably. Which combination of GCP products should you choose?

Options:

A.  

Cloud Pub/Sub, Cloud Dataflow, and Cloud Storage

B.  

Cloud Pub/Sub, Cloud Dataflow, and Local SSD

C.  

Cloud Pub/Sub, Cloud SQL, and Cloud Storage

D.  

Cloud Load Balancing, Cloud Dataflow, and Cloud Storage

Discussion 0
Question # 4

Flowlogistic’s CEO wants to gain rapid insight into their customer base so his sales team can be better informed in the field. This team is not very technical, so they’ve purchased a visualization tool to simplify the creation of BigQuery reports. However, they’ve been overwhelmed by all thedata in the table, and are spending a lot of money on queries trying to find the data they need. You want to solve their problem in the most cost-effective way. What should you do?

Options:

A.  

Export the data into a Google Sheet for virtualization.

B.  

Create an additional table with only the necessary columns.

C.  

Create a view on the table to present to the virtualization tool.

D.  

Create identity and access management (IAM) roles on the appropriate columns, so only they appear in a query.

Discussion 0
Question # 5

You are developing a new deep teaming model that predicts a customer's likelihood to buy on your ecommerce site. Alter running an evaluation of the model against both the original training data and new test data, you find that your model is overfitting the data. You want to improve the accuracy of the model when predicting new data. What should you do?

Options:

A.  

Increase the size of the training dataset, and increase the number of input features.

B.  

Increase the size of the training dataset, and decrease the number of input features.

C.  

Reduce the size of the training dataset, and increase the number of input features.

D.  

Reduce the size of the training dataset, and decrease the number of input features.

Discussion 0
Question # 6

You have one BigQuery dataset which includes customers' street addresses. You want to retrieve all occurrences of street addresses from the dataset. What should you do?

Options:

A.  

Create a deep inspection job on each table in your dataset with Cloud Data Loss Prevention and create an inspection template that includes the STREET_ADDRESS infoType.

B.  

Create a de-identification job in Cloud Data Loss Prevention and use the masking transformation.

C.  

Write a SQL query in BigQuery by using REGEXP_CONTAINS on all tables in your dataset to find rows where the word "street" appears.

D.  

Create a discovery scan configuration on your organization with Cloud Data Loss Prevention and create an inspection template thatincludes the STREET_ADDRESS infoType.

Discussion 0
Question # 7

You are using Cloud Bigtable to persist and serve stock market data for each of the major indices. To serve the trading application, you need to access only the most recent stock prices that are streaming in How should you design your row key and tables to ensure that you can access the data with the most simple query?

Options:

A.  

Create one unique table for all of the indices, and then use the index and timestamp as the row key design

B.  

Create one unique table for all of the indices, and then use a reverse timestamp as the row key design.

C.  

For each index, have a separate table and use a timestamp as the row key design

D.  

For each index, have a separate table and use a reverse timestamp as the row key design

Discussion 0
Question # 8

You create a new report for your large team in Google Data Studio 360. The report uses Google BigQuery as its data source. It is company policy to ensure employees can view only the data associated with their region, so you create and populate a table for each region. You need to enforce the regional access policy to the data.

Which two actions should you take? (Choose two.)

Options:

A.  

Ensure all the tables are included in global dataset.

B.  

Ensure each table is included in a dataset for a region.

C.  

Adjust the settings for each table to allow a related region-based security group view access.

D.  

Adjust the settings for each view to allow a related region-based security group view access.

E.  

Adjust the settings for each dataset to allow a related region-based security group view access.

Discussion 0
Question # 9

Given the record streams MJTelco is interested in ingesting per day, they are concerned about the cost of Google BigQuery increasing. MJTelco asks you to provide a design solution. They require a single large data table called tracking_table. Additionally, they want to minimize the cost of daily queries while performing fine-grained analysis of each day’s events. They also want to use streaming ingestion. What should you do?

Options:

A.  

Create a table called tracking_table and include a DATE column.

B.  

Create a partitioned table called tracking_table and include a TIMESTAMP column.

C.  

Create sharded tables for each day following the pattern tracking_table_YYYYMMD

D.  

D.  

Create a table called tracking_table with a TIMESTAMP column to represent the day.

Discussion 0
Question # 10

You need to compose visualization for operations teams with the following requirements:

Telemetry must include data from all 50,000 installations for the most recent 6 weeks (sampling once every minute)

The report must not be more than 3 hours delayed from live data.

The actionable report should only show suboptimal links.

Most suboptimal links should be sorted to the top.

Suboptimal links can be grouped and filtered by regional geography.

User response time to load the report must be <5 seconds.

You create a data source to store the last 6 weeks of data, and create visualizations that allow viewers to see multiple date ranges, distinct geographic regions, and unique installation types. You always show the latest data without any changes to your visualizations. You want to avoid creating and updating new visualizations each month. What should you do?

Options:

A.  

Look through the current data and compose a series of charts and tables, one for each possiblecombination of criteria.

B.  

Look through the current data and compose a small set of generalized charts and tables bound to criteria filters that allow value selection.

C.  

Export the data to a spreadsheet, compose a series of charts and tables, one for each possiblecombination of criteria, and spread them across multiple tabs.

D.  

Load the data into relational database tables, write a Google App Engine application that queries all rows, summarizes the data across each criteria, and then renders results using the Google Charts and visualization API.

Discussion 0
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