Microsoft Certified Power Platform Functional Consultant Associate · Free Practice Question Medium
Question 8
Microsoft Dataverse is a cloud-based data storage that allows you to leverage the security and connectivity of Microsoft programs. Microsoft Dataverse connects easily to all aspects of Power Platform so that you can fully control, automate, and strengthen your business.
Which of the following are key concepts to understand when working with Dataverse? (Select all that apply)
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A
Using Dataverse, you can break your data into various environments to better manage and secure important information.
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B
Microsoft Dataverse uses non-relational JSON tables linked with Azure Cosmos and Azure CDN.
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C
Microsoft Dataverse uses standard tables, columns, and relationships to help you build powerful scalable data solutions.
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D
Make your data work for you by splitting it up into logical chunks.
Reveal correct answers
Correct answers: A, C, D
Explanation
Microsoft Dataverse uses standard tables, columns, and relationships to help you build powerful scalable data solutions.
With standard tables and columns, as well as the ability to easily define relationships between your data, Microsoft Dataverse was built for those who need powerful, scalable solutions.
The Common Data Model offers the following benefits:
Structural and semantic consistency across applications and deployments.
Simplified integration and disambiguation of data that’s collected from processes, digital interactions, product telemetry, people interactions, and so on.
A unified shape where data integrations can combine existing enterprise data with other sources and use that data to develop apps or derive insights.
Ability to extend the schema and Common Data Model standard tables to tailor the model to your organization.
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Make your data work for you so that you can get the most of it by splitting it up into logical chunks.
Using Dataverse, you can break your data into various environments to better manage and secure important information.
An environment is a space to store, manage, and share your organization's business data, apps, chatbots, and flows. It also serves as a container to separate apps that might have different roles, security requirements, or target audiences. How you choose to use environments depends on your organization and the apps you're trying to build. For example:
You can choose to only build your apps or chatbots in a single environment.
You might create separate environments that group the test and production versions of your apps or chatbots.
You might create separate environments that correspond to specific teams or departments in your company, each containing the relevant data and apps for each audience.
You might also create separate environments for different global branches of your company.
Types of environments
There are multiple types of environments. The type indicates the purpose of the environment and determines its characteristics. The following table summarizes the current types of environments that you might encounter.
A. Dataverse allows users to create multiple environments to segregate and manage different sets of data. This feature enables users to better control access, security, and configuration settings for specific datasets, ensuring that important information is managed and secured effectively.
B. Microsoft Dataverse primarily uses relational tables to store data, rather than non-relational JSON tables linked with Azure Cosmos and Azure CDN. While Dataverse does offer integration capabilities with Azure services, the platform itself is designed to work with relational data structures for efficient data management and processing.
C. Microsoft Dataverse uses standard tables, columns, and relationships to provide a structured and organized way to store and manage data. By leveraging these standard components, users can easily build powerful and scalable data solutions within the platform.
D. Splitting data into logical chunks allows for better organization and management of data within Microsoft Dataverse. By breaking data into smaller, more manageable pieces, users can optimize performance, improve data retrieval, and enhance overall data processing capabilities.
Discussion
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