Your financial services company is moving to cloud technology and wants to store 50 TB of financial timeseries data in the cloud. This data is updated frequently and new data will be streaming in all the time. Your company also wants to move their existing Apache Hadoop jobs to the cloud to get insights into this data.
Which product should they use to store the data?

• A.Google Cloud Datastore
• B.Google Cloud Storage
• C.Cloud Bigtable
• D.Google BigQuery

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When a Cloud Bigtable node fails, ____ is lost.

• A.all data
• B.no data
• C.the last transaction
• D.the time dimension

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

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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.Compute the hash value of each data entry, and compare it with all historical data.
• C.Store each data entry as the primary key in a separate database and apply an index.
• D.Maintain a database table to store the hash value and other metadata for each data entry.

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Which of the following are examples of hyperparameters? (Select 2 answers.)

• A.Number of hidden layers
• B.Number of nodes in each hidden layer
• C.Biases
• D.Weights

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