Cloud-Digital-Leader Exam Dumps - Google Cloud Certified Questions and Answers

Unstructured data refers to data that does not have a pre-defined data model or schema. Examples include text, images, audio, and video files. Call center transcripts are unstructured data because they are composed of free-form text, which does not follow a specific schema or structure.

Option D: Call center transcripts is correct because it represents unstructured data, as opposed to structured data like customer orders or product ratings.

References:

Google Cloud: Understanding Unstructured Data

Google Cloud Storage Solutions: Managing Unstructured Data

https://cloud.google.com/natural-language

Use entity analysis to find and label fields within a document—including emails, chat, and social media—and then sentiment analysis to understand customer opinions to find actionable product and UX insights.

The correct answer is D. AutoML. Here's why:

Context of the Question: The organization wants to build a solution to detect faulty parts on a production line using a large collection of labeled images (intact or defective parts). They do not have data science expertise, so they need a tool that simplifies the machine learning process.

Google Cloud Product Relevance:

AutoML is a suite of machine learning products that allows users to build custom models easily without needing deep expertise in machine learning or data science. It is designed to simplify the process of training, evaluating, and deploying models, especially in cases like image recognition where labeled datasets are already available.

AutoML Vision, a part of AutoML, would be ideal for this use case as it specifically handles image classification and can easily differentiate between intact and defective parts.

Why Not Other Options:

A. Discovery AI for Retail: This is a solution tailored for retail use cases like product discovery and search optimization, not for manufacturing defect detection.

B. Pre-trained APIs: While pre-trained APIs (like Vision API) can recognize general image patterns, they may not be specific enough for a custom use case like detecting defective parts.

C. Document AI: This service is designed for understanding and processing documents, not for analyzing images.

Google Cloud Digital Leader References:

For more information on AutoML, refer to the AutoML Vision documentation.

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.

References:

Google Cloud Privacy Policy: Data Ownership and Responsibility

Google Cloud Trust Principles: Data Protection and Privacy

The correct answer is B. Platform as a service. Here's why:

Context of the Question: The organization wants to run a custom application in the cloud in a flexible and scalable way without managing any infrastructure.

Google Cloud Product Relevance:

Platform as a Service (PaaS) provides a platform that allows customers to develop, run, and manage applications without dealing with the complexity of building and maintaining the underlying infrastructure.

Google Cloud's App Engine is an example of a PaaS offering. It enables organizations to deploy custom applications in a fully managed environment where scaling, load balancing, and infrastructure management are handled automatically.

Why Not Other Options:

A. Infrastructure as a service: IaaS requires the organization to manage the underlying infrastructure (like virtual machines, networks, and storage), which is not suitable if the organization does not want to manage any infrastructure.

C. Network as a service: NaaS is focused on network connectivity and does not provide the capabilities needed to run custom applications.

D. Software as a service: SaaS provides pre-built applications managed by a provider; it is not suitable for running custom applications.

Google Cloud Digital Leader References:

For more on PaaS, refer to the Google App Engine documentation.

Tensor Processing Units (TPUs) are a type of purpose-built hardware designed specifically to accelerate machine learning workloads, particularly those involving TensorFlow. TPUs provide significant speed and performance improvements over general-purpose CPUs and even GPUs when running complex ML models.

Option C: TPUs is correct because TPUs (Tensor Processing Units) are optimized to accelerate the training of machine learning models developed with TensorFlow, providing faster performance compared to other hardware.

References:

Google Cloud: TPUs Overview

Google Cloud AI and Machine Learning Products: Accelerators for TensorFlow

The correct answer is D. Data access policies. Here's why:

Context of the Question: The organization is deploying applications to the cloud using Platform as a Service (PaaS), which means certain responsibilities are shared between the cloud provider (Google Cloud) and the customer.

Google Cloud Product Relevance:

In the shared responsibility model for PaaS, Google Cloud manages the underlying infrastructure, including physical security, network security, and operations. However, the customer organization is still responsible for managing their data, including defining and enforcing data access policies.

Data access policies involve setting permissions, defining roles, and controlling who can access specific data within the organization, which is a critical component of maintaining data security and privacy.

Why Not Other Options:

A. Physical security: This is managed by the cloud provider (Google Cloud) and includes securing data centers and physical hardware.

B. Network security: While the cloud provider ensures network security within its infrastructure, the customer may have some responsibilities at the application level, but in a PaaS environment, most network security responsibilities are managed by the provider.

C. Operations: In a PaaS model, many operational aspects such as patch management, updates, and scaling are handled by the cloud provider.

Google Cloud Digital Leader References:

Refer to Google Cloud Shared Responsibility Model documentation for a deeper understanding of responsibilities between the provider and the customer.

The Natural Language API from Google Cloud is designed to understand and analyze human language. It can automatically identify and extract key topics, sentiments, and entities from text data, making it ideal for processing large datasets of text transcripts to determine what topics customers care most about.

Option D: Natural Language API is correct because it is specifically built for text analysis, topic modeling, and sentiment analysis.

References:

Google Cloud Natural Language API: Text Analysis and Entity Recognition

Google Cloud AI Solutions: Using Natural Language Processing for Customer Insights

Cloud Trace is supposed to be the correct answer. It's an application performance management tool. It's a Google solution for monitoring application performance. It is a distributed tracing system that helps developers debug or fix and optimize their code