Google spoto sure Pass Exam Professional-data-engineer Pdf by Josh q241 vce pdf

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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:	josh

Question 12

You need to create a data pipeline that copies time-series transaction data so that it can be queried from within BigQuery by your data science team for analysis. Every hour, thousands of transactions are updated with a new status. The size of the intitial dataset is 1.5 PB, and it will grow by 3 TB per day. The data is heavily structured, and your data science team will build machine learning models based on this data. You want to maximize performance and usability for your data science team. Which two strategies should you adopt? Choose 2 answers.

Options:

Denormalize the data as must as possible.

Preserve the structure of the data as much as possible.

Use BigQuery UPDATE to further reduce the size of the dataset.

Develop a data pipeline where status updates are appended to BigQuery instead of updated.

Copy a daily snapshot of transaction data to Cloud Storage and store it as an Avro file. Use BigQuery’s support for external data sources to query.

Discussion

Question 13

You are training a spam classifier. You notice that you are overfitting the training data. Which three actions can you take to resolve this problem? (Choose three.)

Options:

Get more training examples

Reduce the number of training examples

Use a smaller set of features

Use a larger set of features

Increase the regularization parameters

Decrease the regularization parameters

Discussion

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Question 14

You maintain ETL pipelines. You notice that a streaming pipeline running on Dataflow is taking a long time to process incoming data, which causes output delays. You also noticed that the pipeline graph was automatically optimized by Dataflow and merged into one step. You want to identify where the potential bottleneck is occurring. What should you do?

Options:

Insert a Reshuffle operation after each processing step, and monitor the execution details in the Dataflow console.

Log debug information in each ParDo function, and analyze the logs at execution time.

Insert output sinks after each key processing step, and observe the writing throughput of each block.

Verify that the Dataflow service accounts have appropriate permissions to write the processed data to the output sinks

Discussion

Question 15

You are developing an Apache Beam pipeline to extract data from a Cloud SQL instance by using JdbclO. You have two projects running in Google Cloud. The pipeline will be deployed and executed on Dataflow in Project A. The Cloud SQL instance is running jn Project B and does not have a public IP address. After deploying the pipeline, you noticed that the pipeline failed to extract data from the Cloud SQL instance due to connection failure. You verified that VPC Service Controls and shared VPC are not in use in these projects. You want to resolve this error while ensuring that the data does not go through the public internet. What should you do?

Options:

Set up VPC Network Peering between Project A and Project B. Add a firewall rule to allow the peered subnet range to access all instances on the network.

Turn off the external IP addresses on the Dataflow worker. Enable Cloud NAT in Project A.

Set up VPC Network Peering between Project A and Project B. Create a Compute Engine instance without external IP address in Project B on the peered subnet to serve as a proxy server to the Cloud SQL database.

Add the external IP addresses of the Dataflow worker as authorized networks in the Cloud SOL instance.