Data 221-230

You need to set up a new architecture in Google Cloud that can handle your Hadoop workloads and requires minimal changes to your existing orchestration processes. What should you do?

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You want to improve the performance of the visualization queries while minimizing the maintenance overhead of the data preparation pipeline. What should you do?

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You have a streaming pipeline that ingests data from Pub/Sub in production. You need to update this streaming pipeline with improved business logic. You need to ensure that the updated pipeline reprocesses the previous two days of delivered Pub/Sub messages. What should you do? (Choose two.)

• Use the Pub/Sub subscription clear-retry-policy flag.

• Use Pub/Sub Snapshot capture two days before the deployment.

• Create a new Pub/Sub subscription two days before the deployment.

• Use the Pub/Sub subscription retain-acked-messages flag.

• Use Pub/Sub Seek with a timestamp.

You want to ensure that read and write access availability is not impacted, and any changes you make can be deployed quickly. What should you do?

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Your organization has two Google Cloud projects, project A and project B. In project A, you have a Pub/Sub topic that receives data from confidential sources. Only the resources in project A should be able to access the data in that topic. You want to ensure that project B and any future project cannot access data in the project A topic. What should you do?

• Add firewall rules in project A so only traffic from the VPC in project A is permitted.

• Configure VPC Service Controls in the organization with a perimeter around project A.

• Use Identity and Access Management conditions to ensure that only users and service accounts in project A. can access resources in project A.

• Configure VPC Service Controls in the organization with a perimeter around the VPC of project A.

You want to use managed services, while minimizing ETL data processing changes and overhead costs. What should you do?

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Inspecting a few messages show no more than 1 second lag between their eventTimestamp and publishTime. What is the problem and what should you do?

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You are building an ELT solution in BigQuery by using Dataform. You need to perform uniqueness and null value checks on your final tables. What should you do to efficiently integrate these checks into your pipeline?

• Build BigQuery user-defined functions (UDFs).

• Create Dataplex data quality tasks.

• Build Dataform assertions into your code.

• Write a Spark-based stored procedure.

You are looking for a low code solution that can be used by your data science team to quickly cleanse and explore data within Cloud Storage. What should you do?

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You store and analyze your relational data in BigQuery on Google Cloud with all data that resides in US regions. You also have a variety of object stores across Microsoft Azure and Amazon Web Services (AWS), also in US regions. You want to query all your data in BigQuery daily with as little movement of data as possible. What should you do?

• Use BigQuery Data Transfer Service to load files from Azure and AWS into BigQuery.

• Create a Dataflow pipeline to ingest files from Azure and AWS to BigQuery.

• Load files from AWS and Azure to Cloud Storage with Cloud Shell gsutil rsync arguments.

• Use the BigQuery Omni functionality and BigLake tables to query files in Azure and AWS.