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Google Cloud-Digital-Leader Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Innovating with Google Cloud Artificial Intelligence16%- AI and ML fundamentals and business application
- Responsible AI principles and practices
- Use cases for AI in business operations and customer experience
- Google Cloud AI/ML products and tools
Topic 2: Trust and Security with Google Cloud17%- Security principles and shared responsibility model
- Identity and access management
- Risk management and incident response
- Data security, encryption, and compliance
Topic 3: Exploring Data Transformation with Google Cloud17%- Google Cloud data storage and analytics services
- Data-driven decision making and business value
- Data lifecycle management and governance
- Modern data architectures and solutions
Topic 4: Modernize Infrastructure and Applications with Google Cloud17%- Migration and modernization strategies
- Application modernization: containers, Kubernetes, serverless
- Hybrid and multi-cloud environments
- Compute, storage, and networking solutions
Topic 5: Digital Transformation with Google Cloud17%- Google Cloud global infrastructure and resource management
- Cloud service models: IaaS, PaaS, SaaS
- Impact of cloud infrastructure on business flexibility, scalability, and agility
- Cost management and pricing models in Google Cloud
Topic 6: Scaling with Google Cloud Operations16%- Automation and infrastructure as code
- Operational excellence and reliability
- Business continuity and disaster recovery
- Monitoring, logging, and observability tools

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Google Cloud Digital Leader Sample Questions (Q147-Q152):

NEW QUESTION # 147
You are working in a company where you need to store Terabytes of Image Data daily and process them e.g.
Taking photos of the entire planet 24 hours every day with satellite and sending data to data centres to store and process it. Which of the following would be the best combination for your infrastructure.
You are working in a company where you need to store Terabytes of Image Data daily and process them e.g.
Taking photos of the entire planet 24 hours every day with satellite and sending data to data centres to store and process it. Which of the following would be the best combination for your infrastructure.

Answer: C

Explanation:
Explanation
The above is a real world example of a company named Planet, where they sent around 80+ satellites to take pictures of earth every day, 24 hours. They run around 40,000 preemptible VMs concurrently.
Preemptible instances function like normal instances but have the following limitations:
Compute Engine might stop preemptible instances at any time due to system events. The probability that Compute Engine will stop a preemptible instance for a system event is generally low, but might vary from day to day and from zone to zone depending on current conditions.
Compute Engine always stops preemptible instances after they run for 24 hours. Certain actions reset this
24-hour counter.
Preemptible instances are finite Compute Engine resources, so they might not always be available.
Preemptible instances can't live migrate to a regular VM instance, or be set to automatically restart when there is a maintenance event.
Due to the above limitations, preemptible instances are not covered by any Service Level Agreement (and, for clarity, are excluded from the Compute Engine SLA).
The Google Cloud Free Tier credits for Compute Engine do not apply to preemptible instances.
Text Description automatically generated

Reference link- https://cloud.google.com/compute/docs/instances/preemptible


NEW QUESTION # 148
A global organization is developing an application to manage payments and online bank accounts in multiple regions. Each transaction must be handled consistently in their database, and they anticipate almost unlimited growth in the amount of data stored.
Which Google Cloud product should the organization choose?

Answer: D


NEW QUESTION # 149
An organization needs to store daily transactional data such as customer records and purchase history. The data follows a consistent schema and is cross-referenced. Which type of service should the organization use?

Answer: D

Explanation:
Relational databases are ideal for storing transactional data that follows a consistent schema and requires cross-referencing (e.g., customer records and purchase history). They provide ACID (Atomicity, Consistency, Isolation, Durability) compliance, which is essential for reliable transaction processing.
Option C: Relational database is correct because it is specifically designed for structured data with a consistent schema and supports complex queries and cross-referencing of data, which is essential for transactional systems.
References:
* Google Cloud: Cloud SQL and Cloud Spanner (Relational Database Services)
* Google Cloud Database Solutions: Selecting the Right Database


NEW QUESTION # 150
You are a database manager working for a new product that will need millions of reading and writ-ing from the database, with zero downtime, key-value i.e. NoSQL features, no manual steps should be required to ensure consistency, repair data, synchronize writes and deletes, Which of the follow-ing database you choose?

Answer: B

Explanation:
Cloud BigTable
Key features
High throughput at low latency
Bigtable is ideal for storing very large amounts of data in a key-value store and supports high read and write throughput at low latency for fast access to large amounts of data. Throughput scales linearly-you can increase QPS (queries per second) by adding Bigtable nodes. Bigtable is built with proven infrastructure that powers Google products used by billions such as Search and Maps.
Cluster resizing without downtime
Scale seamlessly from thousands to millions of reads/writes per second. Bigtable throughput can be dynamically adjusted by adding or removing cluster nodes without restarting, meaning you can increase the size of a Bigtable cluster for a few hours to handle a large load, then reduce the cluster's size again-all without any downtime.
Flexible, automated replication to optimize any workload
Write data once and automatically replicate where needed with eventual consistency-giving you control for high availability and isolation of reading and write workloads. No manual steps are needed to ensure consistency, repair data, or synchronize writes and deletes. Benefit from a high availability SLA of 99.999% for instances with multi-cluster routing across 3 or more regions (99.9% for single-cluster instances).


NEW QUESTION # 151
Which Google Cloud service or feature lets you build machine learning models using Standard SQL and data in a data warehouse?

Answer: D

Explanation:
BigQuery ML lets you create and execute machine learning models in BigQuery using standard SQL queries.
Reference:
https://cloud.google.com/bigquery-ml/docs/introduction


NEW QUESTION # 152
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