Newest Google Professional-Data-Engineer Practice Questions at Zero Cost

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You are designing a data warehouse in BigQuery to analyze sales data for a telecommunication service provider. You need to create a data model for customers, products, and subscriptions All customers, products, and subscriptions can be updated monthly, but you must maintain a historical record of all dat

a. You plan to use the visualization layer for current and historical reporting. You need to ensure that the data model is simple, easy-to-use. and cost-effective. What should you do?

ACreate a normalized model with tables for each entity. Use snapshots before updates to track historical data

BCreate a normalized model with tables for each entity. Keep all input files in a Cloud Storage bucket to track historical data

CCreate a denormalized model with nested and repeated fields Update the table and use snapshots to track historical data

DCreate a denormalized, append-only model with nested and repeated fields Use the ingestion timestamp to track historical data.

Your team is building a data lake platform on Google Cloud. As a part of the data foundation design, you are planning to store all the raw data in Cloud Storage You are expecting to ingest approximately 25 GB of data a day and your billing department is worried about the increasing cost of storing old dat

a. The current business requirements are:

* The old data can be deleted anytime

* You plan to use the visualization layer for current and historical reporting

* The old data should be available instantly when accessed

* There should not be any charges for data retrieval.

What should you do to optimize for cost?

ACreate the bucket with the Autoclass storage class feature.

BCreate an Object Lifecycle Management policy to modify the storage class for data older than 30 days to nearline, 90 days to coldline. and 365 days to archive storage class. Delete old data as needed.

CCreate an Object Lifecycle Management policy to modify the storage class for data older than 30 days to coldline, 90 days to nearline. and 365 days to archive storage class Delete old data as needed.

DCreate an Object Lifecycle Management policy to modify the storage class for data older than 30 days to nearlme. 45 days to coldline. and 60 days to archive storage class Delete old data as needed.

You are part of a healthcare organization where data is organized and managed by respective data owners in various storage services. As a result of this decentralized ecosystem, discovering and managing data has become difficult You need to quickly identify and implement a cost-optimized solution to assist your organization with the following

* Data management and discovery

* Data lineage tracking

* Data quality validation

How should you build the solution?

AUse BigLake to convert the current solution into a data lake architecture.

BBuild a new data discovery tool on Google Kubernetes Engine that helps with new source onboarding and data lineage tracking.

CUse BigOuery to track data lineage, and use Dataprep to manage data and perform data quality validation.

DUse Dataplex to manage data, track data lineage, and perform data quality validation.

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?

ACreate a transactional database that monitors the pending messages.

BCreate a new Pub/Sub push subscription to monitor the orders processed in the agent's system.

CUse Pub/Sub exactly-once delivery in your pull subscription.

DUse a Deduphcate PTransform in Dataflow before sending the messages to the sales agents.

You have created an external table for Apache Hive partitioned data that resides in a Cloud Storage bucket, which contains a large number of files. You notice that queries against this table are slow You want to improve the performance of these queries What should you do?

AMigrate the Hive partitioned data objects to a multi-region Cloud Storage bucket.

BCreate an individual external table for each Hive partition by using a common table name prefix Use wildcard table queries to reference the partitioned data.

CChange the storage class of the Hive partitioned data objects from Coldline to Standard.

DUpgrade the external table to a BigLake table Enable metadata caching for the table.

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