Question 1

Your team wants to generate a report using BigQuery to identify top-selling products. They want to see the product name along with its total sales, sorted in descending order of total sales. Which SQL query best fits this requirement?

Options :

A : SELECT

product_id,

transaction_amount AS total_sales

FROM

transactions

ORDER BY

total_sales DESC;

B : SELECT

product_name,

COUNT(transaction_id) AS total_sales

FROM

transactions

GROUP BY

product_name

ORDER BY

total_sales DESC;

C : SELECT

product_name,

transaction_amount AS total_sales

FROM

transactions

GROUP BY

product_name;

D : SELECT

product_name,

SUM(transaction_amount) AS total_sales

FROM

transactions

GROUP BY

product_name

ORDER BY

total_sales DESC;

Answer: D

Question 2

Your company stores critical financial data in Cloud Storage. To ensure both high availability and disaster recovery, you need to choose a suitable storage location strategy. The company requires immediate access to data with minimal latency and must comply with data redundancy best practices, ensuring that data is available even in the event of a regional outage. Which of the following options best meets these requirements?

Options :

A : Store data in a dual-region bucket without Turbo replication.

B : Store data in a dual-region bucket with Turbo replication.

C : Store data in a single-region bucket with versioning enabled.

D : Store data in a multi-region bucket in a continent far from the main office location.

Answer: B

Question 3

Your team has developed multiple versions of a machine learning model for predicting product demand, and you want to track, organize, and deploy these models effectively. You decide to use Google Cloud’s Model Registry to manage the models. Which practices will help you organize and use the models efficiently? (Select two)

Options :

A : Delete older model versions from the registry after deploying a new version to keep the registry organized and prevent any accidental use of outdated models.

B : Group all models in the registry under a single name without specifying versions to make it easier to find and deploy the latest model.

C : Register models with version numbers and metadata about each model’s hyperparameters, training data, and performance metrics.

D : Use the "Register Model" feature in the Model Registry to add a unique version tag to each model version, indicating its purpose and stage (e.g., "v1.0 - Development" or "v2.0 - Production").

E : Directly upload models to BigQuery to keep model versions alongside the training data for better organization and accessibility.

Answer: C,D

Question 4

Your organization is assessing its data security requirements on Google Cloud. Which of the following statements accurately describes encryption at rest and its purpose?

Options :

A : Encryption at rest protects data during storage and ensures it cannot be accessed if a device is physically removed or stolen.

B : Encryption at rest uses only asymmetric encryption algorithms for all Google Cloud storage services.

C : Encryption at rest ensures that data is protected from unauthorized access during network transfers to other Google Cloud services.

D : Encryption at rest only encrypts data on databases, while encryption in transit protects data stored on all other storage types.

Answer: A

Question 5

A team is designing a pipeline to ingest large amounts of raw data from multiple external sources into BigQuery for further analysis. They plan to perform basic data transformations, such as removing duplicates and standardizing date formats, before loading the data. Which data manipulation methodology is most suitable for this scenario?

Options :

A : ELT (Extract, Load, Transform)

B : ETB (Extract, Transform, Backup)

C : ETLT (Extract, Transform, Load, Transform)

D : ETL (Extract, Transform, Load)

Answer: D

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