Pass the Google Google Cloud Certified Professional-Data-Engineer Questions and answers with CertsForce

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Viewing questions 31-40 out of questions
Questions # 31:

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.


Questions # 32:

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.


Questions # 33:

Suppose you have a table that includes a nested column called "city" inside a column called "person", but when you try to submit the following query in BigQuery, it gives you an error.

SELECT person FROM `project1.example.table1` WHERE city = "London"

How would you correct the error?

Options:

A.

Add ", UNNEST(person)" before the WHERE clause.


B.

Change "person" to "person.city".


C.

Change "person" to "city.person".


D.

Add ", UNNEST(city)" before the WHERE clause.


Questions # 34:

Which of the following is not true about Dataflow pipelines?

Options:

A.

Pipelines are a set of operations


B.

Pipelines represent a data processing job


C.

Pipelines represent a directed graph of steps


D.

Pipelines can share data between instances


Questions # 35:

When using Cloud Dataproc clusters, you can access the YARN web interface by configuring a browser to connect through a ____ proxy.

Options:

A.

HTTPS


B.

VPN


C.

SOCKS


D.

HTTP


Questions # 36:

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 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?

Options:

A.

ParDo


B.

Sink API


C.

Source API


D.

Data extraction


Questions # 37:

If a dataset contains rows with individual people and columns for year of birth, country, and income, how many of the columns are continuous and how many are categorical?

Options:

A.

1 continuous and 2 categorical


B.

3 categorical


C.

3 continuous


D.

2 continuous and 1 categorical


Questions # 38:

To run a TensorFlow training job on your own computer using Cloud Machine Learning Engine, what would your command start with?

Options:

A.

gcloud ml-engine local train


B.

gcloud ml-engine jobs submit training


C.

gcloud ml-engine jobs submit training local


D.

You can't run a TensorFlow program on your own computer using Cloud ML Engine .


Questions # 39:

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_YYYYMMDD.


D.

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


Questions # 40:

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 possible

combination 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 possible

combination 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.


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Viewing questions 31-40 out of questions