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Google Updated Professional-Data-Engineer Exam Questions and Answers by jonathan

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Google Professional-Data-Engineer Exam Overview :

Exam Name: Google Professional Data Engineer Exam
Exam Code: Professional-Data-Engineer Dumps
Vendor: Google Certification: Google Cloud Certified
Questions: 374 Q&A's Shared By: jonathan
Question 52

Your company has hired a new data scientist who wants to perform complicated analyses across very large datasets stored in Google Cloud Storage and in a Cassandra cluster on Google Compute Engine. The scientist primarily wants to create labelled data sets for machine learning projects, along with some visualization tasks. She reports that her laptop is not powerful enough to perform her tasks and it is slowing her down. You want to help her perform her tasks. What should you do?

Options:

A.

Run a local version of Jupiter on the laptop.

B.

Grant the user access to Google Cloud Shell.

C.

Host a visualization tool on a VM on Google Compute Engine.

D.

Deploy Google Cloud Datalab to a virtual machine (VM) on Google Compute Engine.

Discussion
Question 53

Business owners at your company have given you a database of bank transactions. Each row contains the user ID, transaction type, transaction location, and transaction amount. They ask you to investigate what type of machine learning can be applied to the data. Which three machine learning applications can you use? (Choose three.)

Options:

A.

Supervised learning to determine which transactions are most likely to be fraudulent.

B.

Unsupervised learning to determine which transactions are most likely to be fraudulent.

C.

Clustering to divide the transactions into N categories based on feature similarity.

D.

Supervised learning to predict the location of a transaction.

E.

Reinforcement learning to predict the location of a transaction.

F.

Unsupervised learning to predict the location of a transaction.

Discussion
Question 54

You need to store and analyze social media postings in Google BigQuery at a rate of 10,000 messages per minute in near real-time. Initially, design the application to use streaming inserts for individual postings. Your application also performs data aggregations right after the streaming inserts. You discover that the queries after streaming inserts do not exhibit strong consistency, and reports from the queries might miss in-flight data. How can you adjust your application design?

Options:

A.

Re-write the application to load accumulated data every 2 minutes.

B.

Convert the streaming insert code to batch load for individual messages.

C.

Load the original message to Google Cloud SQL, and export the table every hour to BigQuery via streaming inserts.

D.

Estimate the average latency for data availability after streaming inserts, and always run queries after waiting twice as long.

Discussion
Question 55

Your company handles data processing for a number of different clients. Each client prefers to use their own suite of analytics tools, with some allowing direct query access via Google BigQuery. You need to secure the data so that clients cannot see each other’s data. You want to ensure appropriate access to the data. Which three steps should you take? (Choose three.)

Options:

A.

Load data into different partitions.

B.

Load data into a different dataset for each client.

C.

Put each client’s BigQuery dataset into a different table.

D.

Restrict a client’s dataset to approved users.

E.

Only allow a service account to access the datasets.

F.

Use the appropriate identity and access management (IAM) roles for each client’s users.

Discussion
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