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| Section | Weight | Objectives |
|---|---|---|
| Digital Transformation with Google Cloud | 17% | - Why cloud technology is revolutionizing business - Digital transformation with Google Cloud |
| Infrastructure and Application Modernization | 17% | - Modernizing IT infrastructure with Google Cloud - Modernizing applications with Google Cloud |
| Innovating with Data and Google Cloud | 17% | - Google Cloud data management solutions - The value of data |
| Understanding Google Cloud Security and Operations | 17% | - Google Cloud security - Google Cloud operations |
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NEW QUESTION # 67
An organization supplies electric car chargers in a nationwide network. They store customer and charging data in BigQuery. They want to efficiently upgrade and maintain their network to reduce waste and achieve their sustainability goals. How can Google Cloud services help the organization?
Answer: A
Explanation:
The correct answer is D. Create a model in BigQuery to predict future maintenance schedules. Here's why:
Context of the Questio n : The organization wants to use Google Cloud services to efficiently upgrade and maintain their network to reduce waste and achieve sustainability goals.
Google Cloud Product Relevance:
BigQuery is a fully managed data warehouse that supports SQL queries for analyzing large datasets. It also has built-in machine learning capabilities (BigQuery ML) that allow users to create and train models directly within the database using SQL.
By creating a predictive model in BigQuery, the organization can analyze historical data to forecast future maintenance needs, optimize upgrade schedules, and minimize waste, aligning with their sustainability goals.
Why Not Other Options:
A . Secure data access by using Identity and Access Management: While IAM is important for securing access, it does not directly help with maintenance prediction or sustainability goals.
B . Move data from BigQuery to Cloud Storage to reduce storage costs: This option focuses on cost savings, not on improving operational efficiency or achieving sustainability goals.
C . Provide access to third-party developers by creating an API using Apigee: This is not directly related to the goal of optimizing maintenance and reducing waste.
Google Cloud Digital Leader Reference:
Refer to BigQuery ML documentation to learn how to create and use machine learning models within BigQuery.
NEW QUESTION # 68
An organization needs frequent access to only a subset of their dat
a. They want to reduce costs by depositing the rest of their data across Nearline Coldlme and Archive repositories Which Google Cloud product should the organization use?
Answer: C
Explanation:
Per Google docs, specifically for GCP Cloud Storage there exists four types of storage with one of them, standard storage, being described as "storage for data that is frequently accessed ("hot" data) and/or stored for only brief periods of time." https://cloud.google.com/storage
NEW QUESTION # 69
An organization recently launched a virtual customer support agent, generating vast amounts of text and speech data.
Why should they use a cloud data warehouse to interpret this data?
Answer: C
Explanation:
Real-time data ingestion and updates. A simple and universal solution for continually ingesting your enterprise data into popular cloud-based data warehouses in real time. https://www.qlik.com/us/cloud-data-migration/cloud-data-warehouse
NEW QUESTION # 70
Which of the following is true while creating a boot persistent disk from a snapshot.
Answer: C
Explanation:
Explanation
When you create a virtual machine (VM) instance, you must also create a boot disk for the VM. You can use a public image, a custom image, or a snapshot that was taken from another boot disk. When you create a boot disk, limit the disk size to 2 TB to account for the limitations of MBR partitioning.
Compute Engine automatically creates a boot persistent disk when you create an instance. If you require additional data storage space for your instances, add one or more secondary instance storage options.
You might need to create a standalone boot persistent disk and attach it to an instance later, or resize a boot persistent disk to improve performance and add more space for additional applications or operating system files. That process is described in Add or resize a persistent disk.
As a best practice, do not use regional persistent disks for boot disks. In a failover situation, they do not force-attach to a VM.
After you create a snapshot of a boot persistent disk, you can apply data from that snapshot to new persistent disks. It is only possible to apply data from a snapshot when you first create a persistent disk. You cannot apply a snapshot to an existing persistent disk, or apply a snapshot to persistent disks that belong to a different project than that snapshot.
NEW QUESTION # 71
Your customer has reliable information to indicate that they will use a certain amount of computing and analytics. The workloads are critical and they don't want to take a chance with VMs or BigQuery slots being unavailable during a peak period. How can they ensure that they allocate the capacity?
Answer: C
Explanation:
Create reservations on Compute Engine and BigQuery. You can reserve capacity in advance and use it over a period of time. You could also get a cost advantage.
=> There is no need for involved support. It is self-serve via the console.
=> You can reserve resources in advance when you have the need for it. And when you want to take a pay-per-use approach, that is also possible.
=> It is not a good idea to be lock in/hoard resources; you'll pay unnecessarily for resources. Also, it is difficult to time exactly when the demand will be.
References:
https://cloud.google.com/compute/docs/instances/reserving-zonal-resources
https://cloud.google.com/bigquery/docs/reservations-intro
NEW QUESTION # 72
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