Google Certified Professional Data Engineer - Professional-Data-Engineer FREE EXAM DUMPS QUESTIONS & ANSWERS]

Question 1

You are configuring networking for a Dataflow job. The data pipeline uses custom container images with the libraries that are required for the transformation logic preinstalled. The data pipeline reads the data from Cloud Storage and writes the data to BigQuery. You need to ensure cost-effective and secure communication between the pipeline and Google APIs and services.
What should you do?

A. Disable external IP addresses from worker VMs and enable Private Google Access. B. Enable Cloud NAT to provide outbound internet connectivity while enforcing firewall rules. C. Disable external IP addresses and establish a Private Service Connect endpoint IP address. D. Leave external IP addresses assigned to worker VMs while enforcing firewall rules.

Discussion 0

Correct Answer: A Vote an answer

Explanation: Only visible for FreeCram members. You can sign-up / login (it's free).

Question 2

You are preparing data that your machine learning team will use to train a model using BigQueryML. They want to predict the price per square foot of real estate. The training data has a column for the price and a column for the number of square feet. Another feature column called
'feature1' contains null values due to missing data. You want to replace the nulls with zeros to keep more data points. Which query should you use?

A.

B.

C.

D.

Discussion 0

Correct Answer: B Vote an answer

Question 3

Your team has created several BigQuery curated datasets containing anonymized industry benchmark data. You want to make these datasets easily discoverable and accessible for querying by external partner companies within their own Google Cloud projects. You need a secure and scalable solution. What should you do?

A. Create authorized views for each dataset and grant access to each partner. B. Grant the roles/bigquery.dataViewer IAM role to the partner group email addresses on the datasets. C. Export the datasets to partner-specific Cloud Storage buckets. D. Publish the datasets as listings within BigQuery sharing (Analytics Hub).

Discussion 0

Correct Answer: D Vote an answer

Explanation: Only visible for FreeCram members. You can sign-up / login (it's free).

Question 4

Your team is building a data lake platform on Google Cloud. As a part of the data foundation design, you are planning to store all the raw data in Cloud Storage. You are expecting to ingest approximately 25 GB of data a day and your billing department is worried about the increasing cost of storing old data. The current business requirements are:
- The old data can be deleted anytime.
- There is no predefined access pattern of the old data.
- The old data should be available instantly when accessed.
- There should not be any charges for data retrieval.
What should you do to optimize for cost?

A. Create the bucket with the Autoclass storage class feature. B. Create an Object Lifecycle Management policy to modify the storage class for data older than 30 days to nearline, 45 days to coldline, and 60 days to archive storage class. Delete old data as needed. C. Create an Object Lifecycle Management policy to modify the storage class for data older than 30 days to nearline, 90 days to coldline, and 365 days to archive storage class. Delete old data as needed. D. Create an Object Lifecycle Management policy to modify the storage class for data older than 30 days to coldline, 90 days to nearline, and 365 days to archive storage class. Delete old data as needed.

Discussion 0

Correct Answer: A Vote an answer

Question 5

Your company stores vital operational sales data in a BigQuery dataset in us-central1. Your company requires a disaster recovery plan to restore this data to us-east1 with a recovery point objective (RPO) of 24 hours and a recovery time objective (RTO) of 4 hours if us-central1 experiences an outage. You need to implement the disaster recovery plan while keeping costs and complexity to a minimum. What should you do?

A. Configure BigQuery cross-region dataset replication from ns-central1 to us-east1. B. Manually export data to a CSV file in a multi-regional Cloud Storage bucket daily and use bq load to restore to us-east1. C. Set up continuous queries and Pub/Sub to stream data changes from BigQuery tables in us- central1 to us-east1. D. Take daily BigQuery table snapshots in us-central1.

Discussion 0

Correct Answer: B Vote an answer

Explanation: Only visible for FreeCram members. You can sign-up / login (it's free).

Question 6

You want to store your team's shared tables in a single dataset to make data easily accessible to various analysts. You want to make this data readable but unmodifiable by analysts. At the same time, you want to provide the analysts with individual workspaces in the same project, where they can create and store tables for their own use, without the tables being accessible by other analysts. What should you do?

A. Give analysts the BigQuery Data Viewer role on the shared dataset. Create a dataset for each analyst, and give each analyst the BigQuery Data Editor role at the dataset level for their assigned dataset. B. Give analysts the BigQuery Data Viewer role at the project level. Create a dataset for each analyst, and give each analyst the BigQuery Data Editor role at the project level. C. Give analysts the BigQuery Data Viewer role on the shared dataset. Create one other dataset and give the analysts the BigQuery Data Editor role on that dataset. D. Give analysts the BigQuery Data Viewer role at the project level. Create one other dataset, and give the analysts the BigQuery Data Editor role on that dataset.

Discussion 0

Correct Answer: A Vote an answer

Question 7

Which is not a valid reason for poor Cloud Bigtable performance?

A. There are issues with the network connection. B. The Cloud Bigtable cluster has too many nodes. C. The workload isn't appropriate for Cloud Bigtable. D. The table's schema is not designed correctly.

Discussion 0

Correct Answer: B Vote an answer

Explanation: Only visible for FreeCram members. You can sign-up / login (it's free).

Question 8

You work for a financial institution that lets customers register online. As new customers register, their user data is sent to Pub/Sub before being ingested into BigQuery. For security reasons, you decide to redact your customers' Government issued Identification Number while allowing customer service representatives to view the original values when necessary. What should you do?

A. Before loading the data into BigQuery, use Cloud Data Loss Prevention (DLP) to replace input values with a cryptographic hash. B. Use BigQuery's built-in AEAD encryption to encrypt the SSN column. Save the keys to a new table that is only viewable by permissioned users. C. Before loading the data into BigQuery, use Cloud Data Loss Prevention (DLP) to replace input values with a cryptographic format-preserving encryption token. D. Use BigQuery column-level security. Set the table permissions so that only members of the Customer Service user group can see the SSN column.

Discussion 0

Correct Answer: C Vote an answer

Question 9

You are designing BigQuery tables for large volumes of clickstream event data. Your data analyst team will most frequently query by specific event date ranges and filter by the user ID UUID. You want to optimize table structure for query cost and performance. What should you do?

A. Create an ingestion-time partitioned table and cluster it by the user ID column. B. Partition the table by the event date column and cluster the table by user ID column. C. Partition the table by the user ID column and cluster the table by the event date column. D. Cluster the table by both the event date and the user ID columns.

Discussion 0

Correct Answer: B Vote an answer

Explanation: Only visible for FreeCram members. You can sign-up / login (it's free).

Question 10

Your company uses a proprietary system to send inventory data every 6 hours to a data ingestion service in the cloud. Transmitted data includes a payload of several fields and the timestamp of the transmission. If there are any concerns about a transmission, the system re-transmits the data. How should you deduplicate the data most efficiency?

A. Assign global unique identifiers (GUID) to each data entry. B. Maintain a database table to store the hash value and other metadata for each data entry. C. Store each data entry as the primary key in a separate database and apply an index. D. Compute the hash value of each data entry, and compare it with all historical data.

Discussion 0

Correct Answer: A Vote an answer

Question 11

Which of these statements about exporting data from BigQuery is false?

A. To export more than 1 GB of data, you need to put a wildcard in the destination filename. B. The only compression option available is GZIP. C. Data can only be exported in JSON or Avro format. D. The only supported export destination is Google Cloud Storage.

Discussion 0

Correct Answer: C Vote an answer

Explanation: Only visible for FreeCram members. You can sign-up / login (it's free).

Question 12

You have a BigQuery dataset named "customers". All tables will be tagged by using a Data Catalog tag template named "gdpr". The template contains one mandatory field,
"has_sensitive_data", with a boolean value. All employees must be able to do a simple search and find tables in the dataset that have either true or false in the "has_sensitive_data' field.
However, only the Human Resources (HR) group should be able to see the data inside the tables for which "has_sensitive data" is true. You give the all employees group the bigquery.metadataViewer and bigquery.connectionUser roles on the dataset. You want to minimize configuration overhead. What should you do next?

A. Create the "gdpr" tag template with public visibility. Assign the datacatalog.tagTemplateViewer role on this tag to the all employees group, and assign the bigquery.dataViewer role to the HR group on the tables that contain sensitive data. B. Create the "gdpr" tag template with private visibility. Assign the datacatalog.tagTemplateViewer role on this tag to the all employees group, and assign the bigquery.dataViewer role to the HR group on the tables that contain sensitive data. C. Create the "gdpr" tag template with private visibility. Assign the bigquery.dataViewer role to the HR group on the tables that contain sensitive data. D. Create the "gdpr" tag template with public visibility. Assign the bigquery.dataViewer role to the HR group on the tables that contain sensitive data.

Discussion 0

Correct Answer: D Vote an answer

Question 13

Your company's on-premises Apache Hadoop servers are approaching end-of-life, and IT has decided to migrate the cluster to Google Cloud Dataproc. A like-for-like migration of the cluster would require 50 TB of Google Persistent Disk per node. The CIO is concerned about the cost of using that much block storage. You want to minimize the storage cost of the migration. What should you do?

A. Tune the Cloud Dataproc cluster so that there is just enough disk for all data. B. Migrate some of the cold data into Google Cloud Storage, and keep only the hot data in Persistent Disk. C. Put the data into Google Cloud Storage. D. Use preemptible virtual machines (VMs) for the Cloud Dataproc cluster.

Discussion 0

Correct Answer: C Vote an answer

Explanation: Only visible for FreeCram members. You can sign-up / login (it's free).

Question 14

An organization maintains a Google BigQuery dataset that contains tables with user-level data.
They want to expose aggregates of this data to other Google Cloud projects, while still controlling access to the user- level data. Additionally, they need to minimize their overall storage cost and ensure the analysis cost for other projects is assigned to those projects. What should they do?

A. Create and share a new dataset and table that contains the aggregate results. B. Create and share a new dataset and view that provides the aggregate results. C. Create and share an authorized view that provides the aggregate results. D. Create dataViewer Identity and Access Management (IAM) roles on the dataset to enable sharing.

Discussion 0

Correct Answer: C Vote an answer

Explanation: Only visible for FreeCram members. You can sign-up / login (it's free).

Question 15

You have data located in BigQuery that is used to generate reports for your company. You have noticed some weekly executive report fields do not correspond to format according to company standards. For example, report errors include different telephone formats and different country code identifiers. This is a frequent issue, so you need to create a recurring job to normalize the data. You want a quick solution that requires no coding. What should you do?

A. Use BigQuery and GoogleSQL to normalize the data, and schedule recurring queries in BigQuery. B. Use Cloud Data Fusion and Wrangler to normalize the data, and set up a recurring job. C. Create a Spark job and submit it to Dataproc Serverless. D. Use Dataflow SQL to create a job that normalizes the data, and that after the first run of the job, schedule the pipeline to execute recurrently.

Discussion 0

Correct Answer: B Vote an answer