You are building a new data pipeline to share data between two different types of applications: jobs generators and job runners. Your solution must scale to accommodate increases in usage and must accommodate the addition of new applications without negatively affecting the performance of existing ones. What should you do?

• A.Create a table on Cloud SQL, and insert and delete rows with the job information
• B.Create an API using App Engine to receive and send messages to the applications
• C.Create a table on Cloud Spanner, and insert and delete rows with the job information
• D.Use a Cloud Pub/Sub topic to publish jobs, and use subscriptions to execute them

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You create a new report for your large team in Google Data Studio 360. The report uses Google BigQuery as its data source. It is company policy to ensure employees can view only the data associated with their region, so you create and populate a table for each region. You need to enforce the regional access policy to the data.
Which two actions should you take? (Choose two.)

• A.Adjust the settings for each table to allow a related region-based security group view access.
• B.Adjust the settings for each view to allow a related region-based security group view access.
• C.Ensure all the tables are included in global dataset.
• D.Ensure each table is included in a dataset for a region.
• E.Adjust the settings for each dataset to allow a related region-based security group view access.

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You're using Bigtable for a real-time application, and you have a heavy load that is a mix of read and writes.
You've recently identified an additional use case and need to perform hourly an analytical job to calculate certain statistics across the whole database. You need to ensure both the reliability of your production application as well as the analytical workload.
What should you do?

• A.Export Bigtable dump to GCS and run your analytical job on top of the exported files.
• B.Add a second cluster to an existing instance with a multi-cluster routing, use live-traffic app profile for your regular workload and batch-analytics profile for the analytics workload.
• C.Increase the size of your existing cluster twice and execute your analytics workload on your new resized cluster.
• D.Add a second cluster to an existing instance with a single-cluster routing, use live-traffic app profile for your regular workload and batch-analytics profile for the analytics workload.

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Your team is responsible for developing and maintaining ETLs in your company. One of your Dataflow jobs is failing because of some errors in the input data, and you need to improve reliability of the pipeline (incl.
being able to reprocess all failing data).
What should you do?

• A.Add a filtering step to skip these types of errors in the future, extract erroneous rows from logs.
• B.Add a try... catch block to your DoFn that transforms the data, extract erroneous rows from logs.
• C.Add a try... catch block to your DoFn that transforms the data, write erroneous rows to PubSub directly from the DoFn.
• D.Add a try... catch block to your DoFn that transforms the data, use a sideOutput to create a PCollection that can be stored to PubSub later.

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Which of the following is NOT true about Dataflow pipelines?

• A.Dataflow pipelines are tied to Dataflow, and cannot be run on any other runner
• B.Dataflow pipelines can consume data from other Google Cloud services
• C.Dataflow pipelines can be programmed in Java
• D.Dataflow pipelines use a unified programming model, so can work both with streaming and batch data sources

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