Pass the Google Google Cloud Certified Cloud-Digital-Leader Questions and answers with CertsForce

Sustained-use discounts are automatically applied by Google Cloud when Compute Engine instances are run for a significant portion of the month. These discounts do not require any prior commitment or action from the customer; they are automatically calculated based on usage.

Option B: Nothing. Sustained use discounts are automatically applied is correct because Google Cloud automatically grants these discounts based on usage patterns.

The correct answer is B. Use BigQuery ML and create models using SQL. Here's why:

Context of the Question: The organization wants to predict property popularity for the upcoming busy season but does not have a data science team and relies on in-house database administration skills.

Google Cloud Product Relevance:

BigQuery ML enables data analysts and database administrators to build and run machine learning models using SQL queries directly within BigQuery. This makes it accessible to users familiar with SQL, eliminating the need for advanced data science skills.

BigQuery ML is ideal for this organization since it allows them to leverage their existing SQL skills to build predictive models without the complexity of custom machine learning frameworks or coding in languages like Python.

Why Not Other Options:

A. Use custom training in Vertex AI with TensorFlow: This requires expertise in TensorFlow and machine learning, which the organization lacks.

C. Build a model in AutoML using labeled data: AutoML does simplify the ML model-building process but still requires more knowledge than basic SQL. Also, BigQuery ML allows the use of existing SQL skills, which is preferred in this scenario.

D. Integrate pre-trained APIs into their application: Pre-trained APIs are suitable for common use cases like image recognition or natural language processing, not for custom predictions based on unique data like property popularity.

Google Cloud Digital Leader References:

Refer to BigQuery ML documentation for more details on using SQL to create and use ML models.

Physical measures like height, weight, blood pressure, blood type, and stage of the disease can be recorded numerically and they are structured.

When data is uploaded to Google Cloud, the customer retains full ownership of their data. Google Cloud acts as the data processor, providing the infrastructure and services for storage, but the rights to the data, including access, control, and management, remain with the customer.

Option B: The customer is correct because, according to Google Cloud's data privacy policy, the customer owns their data.

The correct answer is B. Machine learning. Here’s why:

Context of the Question: The question describes an application that can diagnose medical conditions based on images submitted by users. This is a task typically handled by machine learning (ML) models, specifically those focused on image recognition and classification.

Google Cloud Product Relevance:

Machine learning (ML) is the correct service because it refers to the use of Google Cloud's AI/ML capabilities, which include services such as AutoML Vision and Vertex AI. These tools can build and deploy machine learning models specifically for image recognition tasks, such as identifying medical conditions from images.

AutoML Vision is designed to create custom ML models with minimal ML expertise, making it suitable for diagnosing medical conditions from images.

Vertex AI allows for training, evaluating, and deploying ML models, including complex models for medical image diagnostics.

Why Not Other Options:

A. App Engine: App Engine is a platform-as-a-service (PaaS) used for building and deploying web applications, not specifically for ML or image recognition tasks.

C. Cloud Logging: Cloud Logging is used to store, search, analyze, and monitor log data and events. It does not have any capabilities related to diagnosing medical conditions or image recognition.

D. Cloud Profiler: Cloud Profiler is a performance analysis tool for applications running in production. It helps identify bottlenecks and optimize resource usage but has no relevance to image diagnosis or machine learning.

Google Cloud Digital Leader References:

For more information on Machine Learning with Google Cloud, refer to the Google Cloud documentation on AutoML Vision and Vertex AI.

Understanding the basic principles and applications of Google Cloud’s ML services is crucial for the Google Cloud Digital Leader exam, which emphasizes knowing how different services solve business challenges.