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PDE — questions

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PDE Question 181

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Topic 1 · Question 181

You need to give new website users a globally unique identifier (GUID) using a service that takes in data points and returns a GUID. This data is sourced from both internal and external systems via HTTP calls that you will make via microservices within your pipeline. There will be tens of thousands of messages per second and that can be multi-threaded. and you worry about the backpressure on the system. How should you design your pipeline to minimize that backpressure?

  • ACall out to the service via HTTP.
  • BCreate the pipeline statically in the class definition.
  • CCreate a new object in the startBundle method of DoFn.
  • DBatch the job into ten-second increments. (correct answer)
Reveal answer & explanation
Correct answer: D

The correct answer is D. Option D: Batch the job into ten-second increments.

Explanation

Google Cloud Batch schedules and runs batch jobs at scale without managing infrastructure.

PDE Question 182

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Topic 1 · Question 182

You are migrating your data warehouse to Google Cloud and decommissioning your on-premises data center. Because this is a priority for your company, you know that bandwidth will be made available for the initial data load to the cloud. The files being transferred are not large in number, but each file is 90 GB. Additionally, you want your transactional systems to continually update the warehouse on Google Cloud in real time. What tools should you use to migrate the data and ensure that it continues to write to your warehouse?

  • AStorage Transfer Service for the migration; Pub/Sub and Cloud Data Fusion for the real-time updates
  • BBigQuery Data Transfer Service for the migration; Pub/Sub and Dataproc for the real-time updates
  • Cgsutil for the migration; Pub/Sub and Dataflow for the real-time updates (correct answer)
  • Dgsutil for both the migration and the real-time updates
Reveal answer & explanation
Correct answer: C

The correct answer is C. Option C: gsutil for the migration; Pub/Sub and Dataflow for the real-time updates

Explanation

Dataflow runs serverless Apache Beam pipelines for stream and batch data processing with autoscaling. Pub/Sub is a serverless, global messaging service that decouples services and ingests high-volume event streams. This option meets the real-time / low-latency performance requirement.

PDE Question 183

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Topic 1 · Question 183

You are using Bigtable to persist and serve stock market data for each of the major indices. To serve the trading application, you need to access only the most recent stock prices that are streaming in. How should you design your row key and tables to ensure that you can access the data with the simplest query?

  • ACreate one unique table for all of the indices, and then use the index and timestamp as the row key design.
  • BCreate one unique table for all of the indices, and then use a reverse timestamp as the row key design.
  • CFor each index, have a separate table and use a timestamp as the row key design.
  • DFor each index, have a separate table and use a reverse timestamp as the row key design. (correct answer)
Reveal answer & explanation
Correct answer: D

The correct answer is D. Option D: For each index, have a separate table and use a reverse timestamp as the row key design. This option meets the real-time / low-latency performance requirement.

PDE Question 184

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Topic 1 · Question 184

You are building a report-only data warehouse where the data is streamed into BigQuery via the streaming API. Following Google's best practices, you have both a staging and a production table for the data. How should you design your data loading to ensure that there is only one master dataset without affecting performance on either the ingestion or reporting pieces?

  • AHave a staging table that is an append-only model, and then update the production table every three hours with the changes written to staging.
  • BHave a staging table that is an append-only model, and then update the production table every ninety minutes with the changes written to staging.
  • CHave a staging table that moves the staged data over to the production table and deletes the contents of the staging table every three hours. (correct answer)
  • DHave a staging table that moves the staged data over to the production table and deletes the contents of the staging table every thirty minutes.
Reveal answer & explanation
Correct answer: C

The correct answer is C. Option C: Have a staging table that moves the staged data over to the production table and deletes the contents of the staging table every three hours. This option meets the real-time / low-latency performance requirement.

PDE Question 185

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Topic 1 · Question 185

You issue a new batch job to Dataflow. The job starts successfully, processes a few elements, and then suddenly fails and shuts down. You navigate to the Dataflow monitoring interface where you find errors related to a particular DoFn in your pipeline. What is the most likely cause of the errors?

  • AJob validation
  • BExceptions in worker code (correct answer)
  • CGraph or pipeline construction
  • DInsufficient permissions
Reveal answer & explanation
Correct answer: B

The correct answer is B. Option B: Exceptions in worker code.

PDE Question 186

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Topic 1 · Question 186

Your new customer has requested daily reports that show their net consumption of Google Cloud compute resources and who used the resources. You need to quickly and efficiently generate these daily reports. What should you do?

  • ADo daily exports of Cloud Logging data to BigQuery. Create views filtering by project, log type, resource, and user. (correct answer)
  • BFilter data in Cloud Logging by project, resource, and user; then export the data in CSV format.
  • CFilter data in Cloud Logging by project, log type, resource, and user, then import the data into BigQuery.
  • DExport Cloud Logging data to Cloud Storage in CSV format. Cleanse the data using Dataprep, filtering by project, resource, and user.
Reveal answer & explanation
Correct answer: A

The correct answer is A. Option A: Do daily exports of Cloud Logging data to BigQuery. Create views filtering by project, log type, resource, and user.

Explanation

BigQuery is a serverless, petabyte-scale data warehouse for fast SQL analytics with no infrastructure to manage. Cloud Logging centralizes, stores, and analyzes logs across services.

PDE Question 187

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Topic 1 · Question 187

The Development and External teams have the project viewer Identity and Access Management (IAM) role in a folder named Visualization. You want the Development Team to be able to read data from both Cloud Storage and BigQuery, but the External Team should only be able to read data from BigQuery. What should you do?

  • ARemove Cloud Storage IAM permissions to the External Team on the acme-raw-data project.
  • BCreate Virtual Private Cloud (VPC) firewall rules on the acme-raw-data project that deny all ingress traffic from the External Team CIDR range.
  • CCreate a VPC Service Controls perimeter containing both projects and BigQuery as a restricted API. Add the External Team users to the perimeter's Access Level.
  • DCreate a VPC Service Controls perimeter containing both projects and Cloud Storage as a restricted API. Add the Development Team users to the perimeter's Access Level. (correct answer)
Reveal answer & explanation
Correct answer: D

The correct answer is D. Option D: Create a VPC Service Controls perimeter containing both projects and Cloud Storage as a restricted API. Add the Development Team users to the perimeter's Access Level.

Explanation

Cloud Storage provides durable, scalable object storage that is fully managed. VPC Service Controls create a security perimeter around managed services to prevent data exfiltration. A VPC provides a global, software-defined private network for your Google Cloud resources.

PDE Question 188

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Topic 1 · Question 188

Your startup has a web application that currently serves customers out of a single region in Asia. You are targeting funding that will allow your startup to serve customers globally. Your current goal is to optimize for cost, and your post-funding goal is to optimize for global presence and performance. You must use a native JDBC driver. What should you do?

  • AUse Cloud Spanner to configure a single region instance initially, and then configure multi-region Cloud Spanner instances after securing funding. (correct answer)
  • BUse a Cloud SQL for PostgreSQL highly available instance first, and Bigtable with US, Europe, and Asia replication after securing funding.
  • CUse a Cloud SQL for PostgreSQL zonal instance first, and Bigtable with US, Europe, and Asia after securing funding.
  • DUse a Cloud SQL for PostgreSQL zonal instance first, and Cloud SQL for PostgreSQL with highly available configuration after securing funding.
Reveal answer & explanation
Correct answer: A

The correct answer is A. Option A: Use Cloud Spanner to configure a single region instance initially, and then configure multi-region Cloud Spanner instances after securing funding.

Explanation

Cloud Spanner is a horizontally scalable, strongly consistent relational database with global reach.

PDE Question 189

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Topic 1 · Question 189

You need to migrate 1 PB of data from an on-premises data center to Google Cloud. Data transfer time during the migration should take only a few hours. You want to follow Google-recommended practices to facilitate the large data transfer over a secure connection. What should you do?

  • AEstablish a Cloud Interconnect connection between the on-premises data center and Google Cloud, and then use the Storage Transfer Service. (correct answer)
  • BUse a Transfer Appliance and have engineers manually encrypt, decrypt, and verify the data.
  • CEstablish a Cloud VPN connection, start gcloud compute scp jobs in parallel, and run checksums to verify the data.
  • DReduce the data into 3 TB batches, transfer the data using gsutil, and run checksums to verify the data.
Reveal answer & explanation
Correct answer: A

The correct answer is A. Option A: Establish a Cloud Interconnect connection between the on-premises data center and Google Cloud, and then use the Storage Transfer Service.

Explanation

Storage Transfer Service moves large datasets into Cloud Storage online with minimal effort. Cloud Interconnect provides a dedicated, private, high-bandwidth link between on premises and Google Cloud.

PDE Question 190

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Topic 1 · Question 190

You are loading CSV files from Cloud Storage to BigQuery. The files have known data quality issues, including mismatched data types, such as STRINGs and INT64s in the same column, and inconsistent formatting of values such as phone numbers or addresses. You need to create the data pipeline to maintain data quality and perform the required cleansing and transformation. What should you do?

  • AUse Data Fusion to transform the data before loading it into BigQuery. (correct answer)
  • BUse Data Fusion to convert the CSV files to a self-describing data format, such as AVRO, before loading the data to BigQuery.
  • CLoad the CSV files into a staging table with the desired schema, perform the transformations with SQL, and then write the results to the final destination table.
  • DCreate a table with the desired schema, load the CSV files into the table, and perform the transformations in place using SQL.
Reveal answer & explanation
Correct answer: A

The correct answer is A. Option A: Use Data Fusion to transform the data before loading it into BigQuery.

Explanation

BigQuery is a serverless, petabyte-scale data warehouse for fast SQL analytics with no infrastructure to manage. Cloud Data Fusion builds ETL/ELT pipelines visually with little code.

PDE Question 191

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Topic 1 · Question 191

You are developing a new deep learning model that predicts a customer's likelihood to buy on your ecommerce site. After running an evaluation of the model against both the original training data and new test data, you find that your model is overfitting the data. You want to improve the accuracy of the model when predicting new data. What should you do?

  • AIncrease the size of the training dataset, and increase the number of input features.
  • BIncrease the size of the training dataset, and decrease the number of input features. (correct answer)
  • CReduce the size of the training dataset, and increase the number of input features.
  • DReduce the size of the training dataset, and decrease the number of input features.
Reveal answer & explanation
Correct answer: B

The correct answer is B. Option B: Increase the size of the training dataset, and decrease the number of input features.

PDE Question 192

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Topic 1 · Question 192

You are implementing a chatbot to help an online retailer streamline their customer service. The chatbot must be able to respond to both text and voice inquiries. You are looking for a low-code or no-cade option, and you want to be able to easily train the chatbot to provide answers to keywords. What should you do?

  • AUse the Cloud Speech-to-Text API to build a Python application in App Engine.
  • BUse the Cloud Speech-to-Text API to build a Python application in a Compute Engine instance.
  • CUse Dialogflow for simple queries and the Cloud Speech-to-Text API for complex queries.
  • DUse Dialogflow to implement the chatbot, defining the intents based on the most common queries collected. (correct answer)
Reveal answer & explanation
Correct answer: D

The correct answer is D. Option D: Use Dialogflow to implement the chatbot, defining the intents based on the most common queries collected.

PDE Question 193

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Topic 1 · Question 193

An aerospace company uses a proprietary data format to store its flight data. You need to connect this new data source to BigQuery and stream the data into BigQuery. You want to efficiently import the data into BigQuery while consuming as few resources as possible. What should you do?

  • AWrite a shell script that triggers a Cloud Function that performs periodic ETL batch jobs on the new data source.
  • BUse a standard Dataflow pipeline to store the raw data in BigQuery, and then transform the format later when the data is used.
  • CUse Apache Hive to write a Dataproc job that streams the data into BigQuery in CSV format.
  • DUse an Apache Beam custom connector to write a Dataflow pipeline that streams the data into BigQuery in Avro format. (correct answer)
Reveal answer & explanation
Correct answer: D

The correct answer is D. Option D: Use an Apache Beam custom connector to write a Dataflow pipeline that streams the data into BigQuery in Avro format.

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.

PDE Question 194

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Topic 1 · Question 194

An online brokerage company requires a high volume trade processing architecture. You need to create a secure queuing system that triggers jobs. The jobs will run in Google Cloud and call the company's Python API to execute trades. You need to efficiently implement a solution. What should you do?

  • AUse a Pub/Sub push subscription to trigger a Cloud Function to pass the data to the Python API. (correct answer)
  • BWrite an application hosted on a Compute Engine instance that makes a push subscription to the Pub/Sub topic.
  • CWrite an application that makes a queue in a NoSQL database.
  • DUse Cloud Composer to subscribe to a Pub/Sub topic and call the Python API.
Reveal answer & explanation
Correct answer: A

The correct answer is A. Option A: Use a Pub/Sub push subscription to trigger a Cloud Function to pass the data to the Python API.

Explanation

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

PDE Question 195

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Topic 1 · Question 195

Your company wants to be able to retrieve large result sets of medical information from your current system, which has over 10 TBs in the database, and store the data in new tables for further query. The database must have a low-maintenance architecture and be accessible via SQL. You need to implement a cost-effective solution that can support data analytics for large result sets. What should you do?

  • AUse Cloud SQL, but first organize the data into tables. Use JOIN in queries to retrieve data.
  • BUse BigQuery as a data warehouse. Set output destinations for caching large queries. (correct answer)
  • CUse a MySQL cluster installed on a Compute Engine managed instance group for scalability.
  • DUse Cloud Spanner to replicate the data across regions. Normalize the data in a series of tables.
Reveal answer & explanation
Correct answer: B

The correct answer is B. Option B: Use BigQuery as a data warehouse. Set output destinations for caching large queries.

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.

PDE Question 196

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Topic 1 · Question 196

You have 15 TB of data in your on-premises data center that you want to transfer to Google Cloud. Your data changes weekly and is stored in a POSIX-compliant source. The network operations team has granted you 500 Mbps bandwidth to the public internet. You want to follow Google-recommended practices to reliably transfer your data to Google Cloud on a weekly basis. What should you do?

  • AUse Cloud Scheduler to trigger the gsutil command. Use the -m parameter for optimal parallelism.
  • BUse Transfer Appliance to migrate your data into a Google Kubernetes Engine cluster, and then configure a weekly transfer job.
  • CInstall Storage Transfer Service for on-premises data in your data center, and then configure a weekly transfer job. (correct answer)
  • DInstall Storage Transfer Service for on-premises data on a Google Cloud virtual machine, and then configure a weekly transfer job.
Reveal answer & explanation
Correct answer: C

The correct answer is C. Option C: Install Storage Transfer Service for on-premises data in your data center, and then configure a weekly transfer job.

Explanation

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

PDE Question 197

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Topic 1 · Question 197

You are designing a system that requires an ACID-compliant database. You must ensure that the system requires minimal human intervention in case of a failure. What should you do?

  • AConfigure a Cloud SQL for MySQL instance with point-in-time recovery enabled.
  • BConfigure a Cloud SQL for PostgreSQL instance with high availability enabled. (correct answer)
  • CConfigure a Bigtable instance with more than one cluster.
  • DConfigure a BigQuery table with a multi-region configuration.
Reveal answer & explanation
Correct answer: B

The correct answer is B. Option B: Configure a Cloud SQL for PostgreSQL instance with high availability enabled.

Explanation

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

PDE Question 198

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Topic 1 · Question 198

You are implementing workflow pipeline scheduling using open source-based tools and Google Kubernetes Engine (GKE). You want to use a Google managed service to simplify and automate the task. You also want to accommodate Shared VPC networking considerations. What should you do?

  • AUse Dataflow for your workflow pipelines. Use Cloud Run triggers for scheduling.
  • BUse Dataflow for your workflow pipelines. Use shell scripts to schedule workflows.
  • CUse Cloud Composer in a Shared VPC configuration. Place the Cloud Composer resources in the host project.
  • DUse Cloud Composer in a Shared VPC configuration. Place the Cloud Composer resources in the service project. (correct answer)
Reveal answer & explanation
Correct answer: D

The correct answer is D. Option D: Use Cloud Composer in a Shared VPC configuration. Place the Cloud Composer resources in the service project.

Explanation

Shared VPC centralizes network administration by sharing one VPC across multiple projects. A VPC provides a global, software-defined private network for your Google Cloud resources. Cloud Composer is managed Apache Airflow for orchestrating multi-step data workflows.

PDE Question 199

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Topic 1 · Question 199

You are using BigQuery and Data Studio to design a customer-facing dashboard that displays large quantities of aggregated data. You expect a high volume of concurrent users. You need to optimize the dashboard to provide quick visualizations with minimal latency. What should you do?

  • AUse BigQuery BI Engine with materialized views. (correct answer)
  • BUse BigQuery BI Engine with logical views.
  • CUse BigQuery BI Engine with streaming data.
  • DUse BigQuery BI Engine with authorized views.
Reveal answer & explanation
Correct answer: A

The correct answer is A. Option A: Use BigQuery BI Engine with materialized views.

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.

PDE Question 200

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Topic 1 · Question 200

Government regulations in the banking industry mandate the protection of clients' personally identifiable information (PII). Your company requires PII to be access controlled, encrypted, and compliant with major data protection standards. In addition to using Cloud Data Loss Prevention (Cloud DLP), you want to follow Google-recommended practices and use service accounts to control access to PII. What should you do?

  • AAssign the required Identity and Access Management (IAM) roles to every employee, and create a single service account to access project resources.
  • BUse one service account to access a Cloud SQL database, and use separate service accounts for each human user.
  • CUse Cloud Storage to comply with major data protection standards. Use one service account shared by all users.
  • DUse Cloud Storage to comply with major data protection standards. Use multiple service accounts attached to IAM groups to grant the appropriate access to each group. (correct answer)
Reveal answer & explanation
Correct answer: D

The correct answer is D. Option D: Use Cloud Storage to comply with major data protection standards. Use multiple service accounts attached to IAM groups to grant the appropriate access to each group.

Explanation

Cloud Storage provides durable, scalable object storage that is fully managed. A service account provides an identity for workloads to access Google Cloud APIs securely. Cloud IAM grants fine-grained, least-privilege access to Google Cloud resources.

Showing questions 181–200 of 341 · Page 10 of 18