Google dumpspedia pearson Professional-data-engineer New Attempt by Jonathan q214 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:	400 Q&A's	Shared By:	jonathan

Question 52

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?

Options:

Specify the TableReference object in the code.

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

Use of both the Google BigQuery TableSchema and TableFieldSchema classes.

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

Discussion

Question 53

An external customer provides you with a daily dump of data from their database. The data flows into Google Cloud Storage GCS as comma-separated values (CSV) files. You want to analyze this data in Google BigQuery, but the data could have rows that are formatted incorrectly or corrupted. How should you build this pipeline?

Options:

Use federated data sources, and check data in the SQL query.

Enable BigQuery monitoring in Google Stackdriver and create an alert.

Import the data into BigQuery using the gcloud CLI and set max_bad_records to 0.

Run a Google Cloud Dataflow batch pipeline to import the data into BigQuery, and push errors to another dead-letter table for analysis.

Discussion

Question 54

Your startup has never implemented a formal security policy. Currently, everyone in the company has access to the datasets stored in Google BigQuery. Teams have freedom to use the service as they see fit, and they have not documented their use cases. You have been asked to secure the data warehouse. You need to discover what everyone is doing. What should you do first?

Options:

Use Google Stackdriver Audit Logs to review data access.

Get the identity and access management IIAM) policy of each table

Use Stackdriver Monitoring to see the usage of BigQuery query slots.

Use the Google Cloud Billing API to see what account the warehouse is being billed to.

Discussion

Question 55

You are deploying 10,000 new Internet of Things devices to collect temperature data in your warehouses globally. You need to process, store and analyze these very large datasets in real time. What should you do?

Options:

Send the data to Google Cloud Datastore and then export to BigQuery.

Send the data to Google Cloud Pub/Sub, stream Cloud Pub/Sub to Google Cloud Dataflow, and store the data in Google BigQuery.

Send the data to Cloud Storage and then spin up an Apache Hadoop cluster as needed in Google Cloud Dataproc whenever analysis is required.

Export logs in batch to Google Cloud Storage and then spin up a Google Cloud SQL instance, import the data from Cloud Storage, and run an analysis as needed.

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