QUESTION: 5

You manage a Cloud Storage bucket that stores temporary files created during data processing. These temporary files are only needed for seven days, after which they are no longer needed. To reduce storage costs and keep your bucket organized, you want to automatically delete these files once they are older than seven days.
What should you do?

Set up a Cloud Scheduler job that invokes a weekly Cloud Run function to delete files older than seven days.
Configure a Cloud Storage lifecycle rule that automatically deletes objects older than seven days.
Develop a batch process using Dataflow that runs weekly and deletes files based on their age.
Create a Cloud Run function that runs daily and deletes files older than seven days.

Answer(s): B

Explanation:

Configuring a Cloud Storage lifecycle rule to automatically delete objects older than seven days is the best solution because:

Built-in feature: Cloud Storage lifecycle rules are specifically designed to manage object lifecycles, such as automatically deleting or transitioning objects based on age.

No additional setup: It requires no external services or custom code, reducing complexity and maintenance.

Cost-effective: It directly achieves the goal of deleting files after seven days without incurring additional compute costs.

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QUESTION: 6

You work for a healthcare company that has a large on-premises data system containing patient records with personally identifiable information (PII) such as names, addresses, and medical diagnoses. You need a standardized managed solution that de-identifies PII across all your data feeds prior to ingestion to Google Cloud.
What should you do?

Use Cloud Run functions to create a serverless data cleaning pipeline. Store the cleaned data in BigQuery.
Use Cloud Data Fusion to transform the data. Store the cleaned data in BigQuery.
Load the data into BigQuery, and inspect the data by using SQL queries. Use Dataflow to transform the data and remove any errors.
Use Apache Beam to read the data and perform the necessary cleaning and transformation operations. Store the cleaned data in BigQuery.

Answer(s): B

Explanation:

Using Cloud Data Fusion is the best solution for this scenario because:

Standardized managed solution: Cloud Data Fusion provides a visual interface for building data pipelines and includes prebuilt connectors and transformations for data cleaning and de- identification.

Compliance: It ensures sensitive data such as PII is de-identified prior to ingestion into Google Cloud, adhering to regulatory requirements for healthcare data.

Ease of use: Cloud Data Fusion is designed for transforming and preparing data, making it a managed and user-friendly tool for this purpose.

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QUESTION: 7

You manage a large amount of data in Cloud Storage, including raw data, processed data, and backups. Your organization is subject to strict compliance regulations that mandate data immutability for specific data types. You want to use an efficient process to reduce storage costs while ensuring that your storage strategy meets retention requirements.
What should you do?

Configure lifecycle management rules to transition objects to appropriate storage classes based on access patterns. Set up Object Versioning for all objects to meet immutability requirements.
Move objects to different storage classes based on their age and access patterns. Use Cloud Key
Management Service (Cloud KMS) to encrypt specific objects with customer-managed encryption keys (CMEK) to meet immutability requirements.
Create a Cloud Run function to periodically check object metadata, and move objects to the appropriate storage class based on age and access patterns. Use object holds to enforce immutability for specific objects.
Use object holds to enforce immutability for specific objects, and configure lifecycle management rules to transition objects to appropriate storage classes based on age and access patterns.

Answer(s): D

Explanation:

Using object holds and lifecycle management rules is the most efficient and compliant strategy for this scenario because:

Immutability: Object holds (temporary or event-based) ensure that objects cannot be deleted or overwritten, meeting strict compliance regulations for data immutability.

Cost efficiency: Lifecycle management rules automatically transition objects to more cost-effective storage classes based on their age and access patterns.

Compliance and automation: This approach ensures compliance with retention requirements while reducing manual effort, leveraging built-in Cloud Storage features.

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QUESTION: 8

You work for an ecommerce company that has a BigQuery dataset that contains customer purchase history, demographics, and website interactions. You need to build a machine learning (ML) model to predict which customers are most likely to make a purchase in the next month. You have limited engineering resources and need to minimize the ML expertise required for the solution.
What should you do?

Use BigQuery ML to create a logistic regression model for purchase prediction.
Use Vertex AI Workbench to develop a custom model for purchase prediction.
Use Colab Enterprise to develop a custom model for purchase prediction.
Export the data to Cloud Storage, and use AutoML Tables to build a classification model for purchase prediction.

Answer(s): A

Explanation:

Using BigQuery ML is the best solution in this case because:

Ease of use: BigQuery ML allows users to build machine learning models using SQL, which requires minimal ML expertise.

Integrated platform: Since the data already exists in BigQuery, there's no need to move it to another service, saving time and engineering resources.

Logistic regression: This is an appropriate model for binary classification tasks like predicting the likelihood of a customer making a purchase in the next month.

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QUESTION: 5

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QUESTION: 6

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QUESTION: 7

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QUESTION: 8

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