Features of Dataverse

1) Security

Dataverse uses Microsoft Azure’s Active Directory(AD) to ensure authenticated access and regulates data security by imposing multi-factor authentication(MFA). Azure AD allows for authentication down to the minutest blocks of the instance (rows and columns) to ensure purely authentic access to data. Auditing capabilities are also provided by Microsoft Dataverse.

2) Logic

Dataverse allows consumers to integrate logical inputs to their business data for directional processing. These logical rules are consistent for every purpose, ranging from redundancy detection to workflow automation.

3)  Data

Dataverse is a platform that offers optimum data flexibility and scalability to model to validate business data. This allows data maximum portability and flexibility. In simpler words, this means that it can be modeled as per the wishes of the user.

4) Storage

Dataverse provides Azure’s fully-scalable storage facilities to the clients. This means that storage is fully-managed from the cloud end and users don’t need to be concerned about outages. Azure’s in-built services help moderate the cloud-spend to provide customized services.

5) Integration

Dataverse ensures interconnectivity with multiple interdisciplinary services that would help improve the quality of data and enable resilient data handling and management. APIs, eventing, and web-hooks help support business data.

What is Microsoft Dataverse?

Microsoft Dataverse is a cloud-based, low-code data platform for deploying business logic to data pipelines. Dataverse offers immense scalability with state-of-the-art security and networking features. It provides flexible solutions for data and business-related problems and is designed to be the prime data repository for business-oriented data. A wealth of Microsoft’s solutions like Microsoft Dynamics 365, Power Automate, and Microsoft Azure support connectivity and congenial compliance with Dataverse. 

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Data is the building block of the modern business landscape. All operations ranging from product marketing to development are centered on the contours of data. Data is generated from a wide variety of sources: applications, services, and even SaaS applications. This huge repository of data needs to be collected, segregated, explored, analyzed and visualized to be harnessed for the good of the organization. Different types of data require different storage and analysis media. This means that you cannot analyze or store unstructured data the same way you analyze and store structured data. Consequently, rigorous data infrastructure is needed to harness the different types of data from different sources so that they could be put to use in the business scenario....

Why Use Dataverse?

All data types supported...

Dataverse Databases

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Features of Dataverse

1) Security...

Relationships in Dataverse

A relationship could be established between multiple tables containing related information to improve the functionality of the solution while boosting its performance at the same time. Multiple tables could be created by splitting a larger table to simplify the workflow by discarding redundant or missing data automatically. Splitting also makes data easy to report and visualize....

Environments in Dataverse

An environment is a virtual space set up by Microsoft Dataverse to store, manage, and share business data particularly integrated with the Power Platform. One Dataverse database could be provisioned per environment. The environment manages access, storage, and security associated with that database....

When Should You Not Integrate Dataverse?

While Dataverse has proven to be an extremely efficient service, there are times when using Dataverse is not required....