Google Updated Associate-Data-Practitioner Exam Questions and Answers by ovie

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.

Defining a newmeasurein LookML to calculate the profit margin using the existing revenue and cost fields is the most efficient and straightforward solution. This approach allows you to dynamically compute the profit margin directly within your Looker Explores and dashboards without needing to pre-calculate or create additional tables. The measure can be defined using LookML syntax, such as:

measure: profit_margin {

type: number

sql: (revenue - cost) / revenue ;;

value_format: "0.0%"

}

This method is quick to implement and integrates seamlessly into your existing Looker model, enabling accurate visualization of profit margins across your products.

Using thebq loadcommand is the simplest and most efficient way to perform a one-time load of files from your local machine into BigQuery. This command-line tool is easy to use, requires minimal setup, and supports direct uploads from local files to BigQuery tables. It meets the requirement for minimal effort while allowing you to quickly demonstrate BigQuery's capabilities to your organization’s leadership team.

For regulatory requirements that mandate complete and manual control of data encryption, you should use customer-supplied encryption keys (CSEK). With CSEK, your company provides the encryption keys for data storage, and Google Cloud does not store or manage these keys. This approach ensures that your organization retains full control and responsibility over the encryption process, meeting strict regulatory compliance requirements.