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How Can You Crack the Google Cloud-Digital-Leader Exam with Flying Colors?
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Google Cloud Digital Leader Exam is an excellent opportunity for professionals who want to enhance their careers in the digital transformation field. Google Cloud Digital Leader certification is recognized globally and is highly valued by employers, making it a great addition to any resume. Moreover, it provides a comprehensive understanding of digital transformation concepts, technologies, and trends, making it an ideal certification for individuals who want to lead their organizations towards a successful digital future.
Google Cloud Digital Leader Certification Exam covers a wide range of topics, including cloud computing architecture, cloud migration, data analytics, machine learning, and leadership skills. Cloud-Digital-Leader Exam assesses the individual's ability to manage and lead teams in the digital world and provide them with the necessary skills to drive innovation and change. Google Cloud Digital Leader certification is ideal for individuals who are leading digital transformation initiatives in their organizations or are looking to build a career in cloud computing and leadership. By passing Cloud-Digital-Leader exam, individuals can demonstrate their expertise in cloud computing and leadership and stand out in the competitive job market.
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Google Cloud Digital Leader Certification Exam covers a wide range of topics, including cloud computing fundamentals, Google Cloud Platform services, data analytics, machine learning, and artificial intelligence. It also tests an individual's ability to design and implement digital transformation strategies and manage change within an organization.
Google Cloud Digital Leader Sample Questions (Q156-Q161):
NEW QUESTION # 156
Your team has developed a machine learning model for your customer. The test results indicate very strong predictive capability. The model is then deployed in production. Evaluation of the predictions in production show that they are off by a pronounced margin. What is the issue and how can you solve for it?
- A. The model is over fitted. Add more features to the model to fix it.
- B. The model is under fitted. Train with less data.
- C. The model is fine since the test results are good. Fix the production of incoming data.
- D. The model is overfitted. Train with more data.
Answer: D
Explanation:
If our ML model does well on the training set than on the production set, then we're likely over fitting. Training with more data would be one solution.
NEW QUESTION # 157
Your organization wants an economical solution to store data such as files, graphical images, and videos and to access and share them securely.
Which Google Cloud product or service should your organization use?
- A. Cloud Spanner
- B. Cloud SQL
- C. Cloud Storage
- D. BigQuery
Answer: C
Explanation:
- Google Storage is GCP's version of AWS Simple Storage Service (S3) and an S3 bucket would be equivalent to a Google Storage bucket across the two clouds
NEW QUESTION # 158
An organization wants to build an entirely new infrastructure and applications in the cloud.
Which application modernization approach should the organization use?
- A. Invent in greenfield.
- B. Change their application, and then move it to the cloud.
- C. Invent in brownfield.
- D. Move the application to the cloud, and then change it.
Answer: A
Explanation:
Explanation
A Greenfield approach is a brand-new implementation , where companies then add their needed configurations and customizations. This approach provides a clean slate to start from, does not carry over needless customizations and technical debt, and provides a solid foundation for business process re-engineering.
A greenfield deployment is the design, installation and configuration of computer infrastructure where none existed before, for example, in a new office. In contrast, a brownfield deployment is an upgrade or addition to existing infrastructure using legacy components.
NEW QUESTION # 159
You are a program manager for a team of developers who are building an event-driven application to allow users to follow one another's activities in the app. Each time a user adds himself as a follower of another user, a write occurs in the real-time database.
The developers will develop a lightweight piece of code that can respond to database writes and generate a notification to let the appropriate users know that they have gained new followers. The code should integrate with other cloud services such as Pub/Sub, Firebase, and Cloud APIs to streamline the orchestration process. The application requires a platform that automatically manages underlying infrastructure and scales to zero when there is no activity.
Which primary compute resource should your developers select, given these requirements?
- A. Compute Engine
- B. App Engine flexible environment
- C. Cloud Functions
- D. Google Kubernetes Engine
Answer: C
Explanation:
Reference:
NEW QUESTION # 160
Considering Google Cloud Storage different Options which of the following is / are correct on the basis of their real world use cases?
- A. Cloud SQL : User Credentials, customer orders.
- B. Google Cloud BigTable : AdTech, Financial and IoT Data.
- C. All of the Above.
- D. Cloud Storage : Images, Large Media, files , backups.
Answer: C
Explanation:
Explanation
Cloud Datastore is the best for semi-structured application data that is used in app engines' applications.
Bigtable is best for analytical data with heavy read/write events like AdTech, Financial or IoT data. Cloud Storage is best for structured and unstructured, binary or object data like images, large media files and backups. SQL is best for web frameworks and in existing applications like storing user credentials and customer orders. Cloud Spanner is best for large scale database applications that are larger than two terabytes; for example, for financial trading and e-commerce use cases. As I mentioned at the beginning of the module, depending on your application, you might use one or several of these services to get the job done.
NEW QUESTION # 161
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