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PDE β€” questions

Page 16 of 18 Β· 341 total questions.

Topic 1 Β· Question 302

You work for a farming company. You have one BigQuery table named sensors, which is about 500 MB and contains the list of your 5000 sensors, with columns for id, name, and location. This table is updated every hour. Each sensor generates one metric every 30 seconds along with a timestamp, which you want to store in BigQuery. You want to run an analytical query on the data once a week for monitoring purposes. You also want to minimize costs. What data model should you use?

  • A1. Create a metrics column in the sensors table.2. Set RECORD type and REPEATED mode for the metrics column.3. Use an UPDATE statement every 30 seconds to add new metrics.
  • B1. Create a metrics column in the sensors table.2. Set RECORD type and REPEATED mode for the metrics column.3. Use an INSERT statement every 30 seconds to add new metrics.
  • C1. Create a metrics table partitioned by timestamp.2. Create a sensorId column in the metrics table, that points to the id column in the sensors table.3. Use an INSERT statement every 30 seconds to append new metrics to the metrics table.4. Join the two tables, if needed, when running the analytical query. (correct answer)
  • D1. Create a metrics table partitioned by timestamp.2. Create a sensorId column in the metrics table, which points to the id column in the sensors table.3. Use an UPDATE statement every 30 seconds to append new metrics to the metrics table.4. Join the two tables, if needed, when running the analytical query.
Reveal answer & explanation
Correct answer: C

The correct answer is C. Option C: 1. Create a metrics table partitioned by timestamp.2. Create a sensorId column in the metrics table, that points to the id column in the sensors table.3. Use an INSERT statement every 30 seconds to append new metrics... This option delivers the requirement at the lowest cost.

Topic 1 Β· Question 303

You are managing a Dataplex environment with raw and curated zones. A data engineering team is uploading JSON and CSV files to a bucket asset in the curated zone but the files are not being automatically discovered by Dataplex. What should you do to ensure that the files are discovered by Dataplex?

  • AMove the JSON and CSV files to the raw zone. (correct answer)
  • BEnable auto-discovery of files for the curated zone.
  • CUse the bg command-line tool to load the JSON and CSV files into BigQuery tables.
  • DGrant object level access to the CSV and JSON files in Cloud Storage.
Reveal answer & explanation
Correct answer: A

The correct answer is A. Option A: Move the JSON and CSV files to the raw zone.

Topic 1 Β· Question 304

You have a table that contains millions of rows of sales data, partitioned by date. Various applications and users query this data many times a minute. The query requires aggregating values by using AVG, MAX, and SUM, and does not require joining to other tables. The required aggregations are only computed over the past year of data, though you need to retain full historical data in the base tables. You want to ensure that the query results always include the latest data from the tables, while also reducing computation cost, maintenance overhead, and duration. What should you do?

  • ACreate a materialized view to aggregate the base table data. Include a filter clause to specify the last one year of partitions. (correct answer)
  • BCreate a materialized view to aggregate the base table data. Configure a partition expiration on the base table to retain only the last one year of partitions.
  • CCreate a view to aggregate the base table data. Include a filter clause to specify the last year of partitions.
  • DCreate a new table that aggregates the base table data. Include a filter clause to specify the last year of partitions. Set up a scheduled query to recreate the new table every hour.
Reveal answer & explanation
Correct answer: A

The correct answer is A. Option A: Create a materialized view to aggregate the base table data. Include a filter clause to specify the last one year of partitions.

Topic 1 Β· Question 305

Your organization uses a multi-cloud data storage strategy, storing data in Cloud Storage, and data in Amazon Web Services’ (AWS) S3 storage buckets. All data resides in US regions. You want to query up-to-date data by using BigQuery, regardless of which cloud the data is stored in. You need to allow users to query the tables from BigQuery without giving direct access to the data in the storage buckets. What should you do?

  • ASetup a BigQuery Omni connection to the AWS S3 bucket data. Create BigLake tables over the Cloud Storage and S3 data and query the data using BigQuery directly. (correct answer)
  • BSet up a BigQuery Omni connection to the AWS S3 bucket data. Create external tables over the Cloud Storage and S3 data and query the data using BigQuery directly.
  • CUse the Storage Transfer Service to copy data from the AWS S3 buckets to Cloud Storage buckets. Create BigLake tables over the Cloud Storage data and query the data using BigQuery directly.
  • DUse the Storage Transfer Service to copy data from the AWS S3 buckets to Cloud Storage buckets. Create external tables over the Cloud Storage data and query the data using BigQuery directly.
Reveal answer & explanation
Correct answer: A

The correct answer is A. Option A: Setup a BigQuery Omni connection to the AWS S3 bucket data. Create BigLake tables over the Cloud Storage and S3 data and query the data using BigQuery directly.

Explanation

Cloud Storage provides durable, scalable object storage that is fully managed. BigQuery is a serverless, petabyte-scale data warehouse for fast SQL analytics with no infrastructure to manage.

Topic 1 Β· Question 306

You are preparing an organization-wide dataset. You need to preprocess customer data stored in a restricted bucket in Cloud Storage. The data will be used to create consumer analyses. You need to comply with data privacy requirements. What should you do?

  • AUse Dataflow and the Cloud Data Loss Prevention API to mask sensitive data. Write the processed data in BigQuery. (correct answer)
  • BUse customer-managed encryption keys (CMEK) to directly encrypt the data in Cloud Storage. Use federated queries from BigQuery. Share the encryption key by following the principle of least privilege.
  • CUse the Cloud Data Loss Prevention API and Dataflow to detect and remove sensitive fields from the data in Cloud Storage. Write the filtered data in BigQuery.
  • DUse Dataflow and Cloud KMS to encrypt sensitive fields and write the encrypted data in BigQuery. Share the encryption key by following the principle of least privilege.
Reveal answer & explanation
Correct answer: A

The correct answer is A. Option A: Use Dataflow and the Cloud Data Loss Prevention API to mask sensitive data. Write the processed data in BigQuery.

Explanation

BigQuery is a serverless, petabyte-scale data warehouse for fast SQL analytics with no infrastructure to manage. Dataflow runs serverless Apache Beam pipelines for stream and batch data processing with autoscaling.

Topic 1 Β· Question 307

You need to connect multiple applications with dynamic public IP addresses to a Cloud SQL instance. You configured users with strong passwords and enforced the SSL connection to your Cloud SQL instance. You want to use Cloud SQL public IP and ensure that you have secured connections. What should you do?

  • AAdd CIDR 0.0.0.0/0 network to Authorized Network. Use Identity and Access Management (IAM) to add users.
  • BAdd all application networks to Authorized Network and regularly update them.
  • CLeave the Authorized Network empty. Use Cloud SQL Auth proxy on all applications. (correct answer)
  • DAdd CIDR 0.0.0.0/0 network to Authorized Network. Use Cloud SQL Auth proxy on all applications.
Reveal answer & explanation
Correct answer: C

The correct answer is C. Option C: Leave the Authorized Network empty. Use Cloud SQL Auth proxy on all applications.

Explanation

Cloud SQL is a managed relational database (MySQL/PostgreSQL/SQL Server) that handles patching, backups, and failover.

Topic 1 Β· Question 308

You are migrating a large number of files from a public HTTPS endpoint to Cloud Storage. The files are protected from unauthorized access using signed URLs. You created a TSV file that contains the list of object URLs and started a transfer job by using Storage Transfer Service. You notice that the job has run for a long time and eventually failed. Checking the logs of the transfer job reveals that the job was running fine until one point, and then it failed due to HTTP 403 errors on the remaining files. You verified that there were no changes to the source system. You need to fix the problem to resume the migration process. What should you do?

  • ASet up Cloud Storage FUSE, and mount the Cloud Storage bucket on a Compute Engine instance. Remove the completed files from the TSV file. Use a shell script to iterate through the TSV file and download the remaining URLs to the FUSE mount point.
  • BRenew the TLS certificate of the HTTPS endpoint. Remove the completed files from the TSV file and rerun the Storage Transfer Service job.
  • CCreate a new TSV file for the remaining files by generating signed URLs with a longer validity period. Split the TSV file into multiple smaller files and submit them as separate Storage Transfer Service jobs in parallel. (correct answer)
  • DUpdate the file checksums in the TSV file from using MD5 to SHA256. Remove the completed files from the TSV file and rerun the Storage Transfer Service job.
Reveal answer & explanation
Correct answer: C

The correct answer is C. Option C: Create a new TSV file for the remaining files by generating signed URLs with a longer validity period. Split the TSV file into multiple smaller files and submit them as separate Storage Transfer Service jobs in parallel.

Explanation

Storage Transfer Service moves large datasets into Cloud Storage online with minimal effort.

Topic 1 Β· Question 309

You work for an airline and you need to store weather data in a BigQuery table. Weather data will be used as input to a machine learning model. The model only uses the last 30 days of weather data. You want to avoid storing unnecessary data and minimize costs. What should you do?

  • ACreate a BigQuery table where each record has an ingestion timestamp. Run a scheduled query to delete all the rows with an ingestion timestamp older than 30 days.
  • BCreate a BigQuery table partitioned by datetime value of the weather date. Set up partition expiration to 30 days. (correct answer)
  • CCreate a BigQuery table partitioned by ingestion time. Set up partition expiration to 30 days.
  • DCreate a BigQuery table with a datetime column for the day the weather data refers to. Run a scheduled query to delete rows with a datetime value older than 30 days.
Reveal answer & explanation
Correct answer: B

The correct answer is B. Option B: Create a BigQuery table partitioned by datetime value of the weather date. Set up partition expiration to 30 days.

Explanation

BigQuery is a serverless, petabyte-scale data warehouse for fast SQL analytics with no infrastructure to manage. This option delivers the requirement at the lowest cost.

Topic 1 Β· Question 310

You need to look at BigQuery data from a specific table multiple times a day. The underlying table you are querying is several petabytes in size, but you want to filter your data and provide simple aggregations to downstream users. You want to run queries faster and get up-to-date insights quicker. What should you do?

  • ARun a scheduled query to pull the necessary data at specific intervals dally.
  • BUse a cached query to accelerate time to results.
  • CLimit the query columns being pulled in the final result.
  • DCreate a materialized view based off of the query being run. (correct answer)
Reveal answer & explanation
Correct answer: D

The correct answer is D. Option D: Create a materialized view based off of the query being run.

Topic 1 Β· Question 311

Your chemical company needs to manually check documentation for customer order. You use a pull subscription in Pub/Sub so that sales agents get details from the order. You must ensure that you do not process orders twice with different sales agents and that you do not add more complexity to this workflow. What should you do?

  • AUse a Deduplicate PTransform in Dataflow before sending the messages to the sales agents.
  • BCreate a transactional database that monitors the pending messages.
  • CUse Pub/Sub exactly-once delivery in your pull subscription. (correct answer)
  • DCreate a new Pub/Sub push subscription to monitor the orders processed in the agent's system.
Reveal answer & explanation
Correct answer: C

The correct answer is C. Option C: Use Pub/Sub exactly-once delivery in your pull subscription.

Explanation

Pub/Sub is a serverless, global messaging service that decouples services and ingests high-volume event streams.

Topic 1 Β· Question 312

You are migrating your on-premises data warehouse to BigQuery. As part of the migration, you want to facilitate cross-team collaboration to get the most value out of the organization’s data. You need to design an architecture that would allow teams within the organization to securely publish, discover, and subscribe to read-only data in a self-service manner. You need to minimize costs while also maximizing data freshness. What should you do?

  • AUse Analytics Hub to facilitate data sharing. (correct answer)
  • BCreate authorized datasets to publish shared data in the subscribing team's project.
  • CCreate a new dataset for sharing in each individual team’s project. Grant the subscribing team the bigquery.dataViewer role on the dataset.
  • DUse BigQuery Data Transfer Service to copy datasets to a centralized BigQuery project for sharing.
Reveal answer & explanation
Correct answer: A

The correct answer is A. Option A: Use Analytics Hub to facilitate data sharing. This option delivers the requirement at the lowest cost.

Topic 1 Β· Question 313

You want to migrate an Apache Spark 3 batch job from on-premises to Google Cloud. You need to minimally change the job so that the job reads from Cloud Storage and writes the result to BigQuery. Your job is optimized for Spark, where each executor has 8 vCPU and 16 GB memory, and you want to be able to choose similar settings. You want to minimize installation and management effort to run your job. What should you do?

  • AExecute the job as part of a deployment in a new Google Kubernetes Engine cluster.
  • BExecute the job from a new Compute Engine VM.
  • CExecute the job in a new Dataproc cluster.
  • DExecute as a Dataproc Serverless job. (correct answer)
Reveal answer & explanation
Correct answer: D

The correct answer is D. Option D: Execute as a Dataproc Serverless job.

Explanation

Dataproc runs managed Spark and Hadoop clusters for big-data processing.

Topic 1 Β· Question 314

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?

  • ADisable external IP addresses from worker VMs and enable Private Google Access. (correct answer)
  • BLeave external IP addresses assigned to worker VMs while enforcing firewall rules.
  • CDisable external IP addresses and establish a Private Service Connect endpoint IP address.
  • DEnable Cloud NAT to provide outbound internet connectivity while enforcing firewall rules.
Reveal answer & explanation
Correct answer: A

The correct answer is A. Option A: Disable external IP addresses from worker VMs and enable Private Google Access.

Explanation

Private Google Access lets internal instances reach Google APIs without external IPs. This option delivers the requirement at the lowest cost.

Topic 1 Β· Question 315

You are using Workflows to call an API that returns a 1KB JSON response, apply some complex business logic on this response, wait for the logic to complete, and then perform a load from a Cloud Storage file to BigQuery. The Workflows standard library does not have sufficient capabilities to perform your complex logic, and you want to use Python's standard library instead. You want to optimize your workflow for simplicity and speed of execution. What should you do?

  • ACreate a Cloud Composer environment and run the logic in Cloud Composer.
  • BCreate a Dataproc cluster, and use PySpark to apply the logic on your JSON file.
  • CInvoke a Cloud Function instance that uses Python to apply the logic on your JSON file. (correct answer)
  • DInvoke a subworkflow in Workflows to apply the logic on your JSON file.
Reveal answer & explanation
Correct answer: C

The correct answer is C. Option C: Invoke a Cloud Function instance that uses Python to apply the logic on your JSON file.

Topic 1 Β· Question 316

You are administering a BigQuery on-demand environment. Your business intelligence tool is submitting hundreds of queries each day that aggregate a large (50 TB) sales history fact table at the day and month levels. These queries have a slow response time and are exceeding cost expectations. You need to decrease response time, lower query costs, and minimize maintenance. What should you do?

  • ABuild authorized views on top of the sales table to aggregate data at the day and month level.
  • BEnable BI Engine and add your sales table as a preferred table.
  • CBuild materialized views on top of the sales table to aggregate data at the day and month level. (correct answer)
  • DCreate a scheduled query to build sales day and sales month aggregate tables on an hourly basis.
Reveal answer & explanation
Correct answer: C

The correct answer is C. Option C: Build materialized views on top of the sales table to aggregate data at the day and month level.

Topic 1 Β· Question 317

You have several different unstructured data sources, within your on-premises data center as well as in the cloud. The data is in various formats, such as Apache Parquet and CSV. You want to centralize this data in Cloud Storage. You need to set up an object sink for your data that allows you to use your own encryption keys. You want to use a GUI-based solution. What should you do?

  • AUse BigQuery Data Transfer Service to move files into BigQuery.
  • BUse Storage Transfer Service to move files into Cloud Storage
  • CUse Dataflow to move files into Cloud Storage
  • DUse Cloud Data Fusion to move files into Cloud Storage. (correct answer)
Reveal answer & explanation
Correct answer: D

The correct answer is D. Option D: Use Cloud Data Fusion to move files into Cloud Storage.

Explanation

Cloud Storage provides durable, scalable object storage that is fully managed. Cloud Data Fusion builds ETL/ELT pipelines visually with little code.

Topic 1 Β· Question 318

You are using BigQuery with a regional dataset that includes a table with the daily sales volumes. This table is updated multiple times per day. You need to protect your sales table in case of regional failures with a recovery point objective (RPO) of less than 24 hours, while keeping costs to a minimum. What should you do?

  • ASchedule a daily export of the table to a Cloud Storage dual or multi-region bucket. (correct answer)
  • BSchedule a daily copy of the dataset to a backup region.
  • CSchedule a daily BigQuery snapshot of the table.
  • DModify ETL job to load the data into both the current and another backup region.
Reveal answer & explanation
Correct answer: A

The correct answer is A. Option A: Schedule a daily export of the table to a Cloud Storage dual or multi-region bucket.

Explanation

Cloud Storage provides durable, scalable object storage that is fully managed.

Topic 1 Β· Question 319

You are preparing an organization-wide dataset. You need to preprocess customer data stored in a restricted bucket in Cloud Storage. The data will be used to create consumer analyses. You need to follow data privacy requirements, including protecting certain sensitive data elements, while also retaining all of the data for potential future use cases. What should you do?

  • AUse the Cloud Data Loss Prevention API and Dataflow to detect and remove sensitive fields from the data in Cloud Storage. Write the filtered data in BigQuery.
  • BUse customer-managed encryption keys (CMEK) to directly encrypt the data in Cloud Storage. Use federated queries from BigQuery. Share the encryption key by following the principle of least privilege.
  • CUse Dataflow and the Cloud Data Loss Prevention API to mask sensitive data. Write the processed data in BigQuery. (correct answer)
  • DUse Dataflow and Cloud KMS to encrypt sensitive fields and write the encrypted data in BigQuery. Share the encryption key by following the principle of least privilege.
Reveal answer & explanation
Correct answer: C

The correct answer is C. Option C: Use Dataflow and the Cloud Data Loss Prevention API to mask sensitive data. Write the processed data in BigQuery.

Explanation

BigQuery is a serverless, petabyte-scale data warehouse for fast SQL analytics with no infrastructure to manage. Dataflow runs serverless Apache Beam pipelines for stream and batch data processing with autoscaling.

Topic 1 Β· Question 320

Your company uses Looker Studio connected to BigQuery for reporting. Users are experiencing slow dashboard load times due to complex queries on a large table. The queries involve aggregations and filtering on several columns. You need to optimize query performance to decrease the dashboard load times. What should you do?

  • AConfigure Looker Studio to use a shorter data refresh interval to ensure fresh data is always displayed.
  • BCreate a materialized view in BigQuery that pre-calculates the aggregations and filters used in the Looker Studio dashboards.
  • CImplement row-level security in BigQuery to restrict data access and reduce the amount of data processed by the queries.
  • DUse BigQuery BI Engine to accelerate query performance by caching frequently accessed data. (correct answer)
Reveal answer & explanation
Correct answer: D

The correct answer is D. Option D: Use BigQuery BI Engine to accelerate query performance by caching frequently accessed data.

Explanation

BigQuery BI Engine accelerates dashboards with an in-memory analysis layer. BigQuery is a serverless, petabyte-scale data warehouse for fast SQL analytics with no infrastructure to manage.

Topic 1 Β· Question 321

Your company is planning to migrate a large on-premises data warehouse to BigQuery. The data is currently stored in a proprietary, vendor-specific format. You need to perform a batch migration of this data to BigQuery. What should you do?

  • AUse the bq command-line tool to load the data directly from the on-premises data warehouse.
  • BExport the data to CSV files, upload the files to Cloud Storage, then load the files into BigQuery.
  • CUse the BigQuery Data Transfer Service. (correct answer)
  • DUse Datastream to replicate the data in real time.
Reveal answer & explanation
Correct answer: C

The correct answer is C. Option C: Use the BigQuery Data Transfer Service.

Explanation

BigQuery is a serverless, petabyte-scale data warehouse for fast SQL analytics with no infrastructure to manage. BigQuery Data Transfer Service automates loading data into BigQuery on a schedule.

Showing questions 301–320 of 341 Β· Page 16 of 18