Dataverse is more than a passive database; it is a container of data and an application platform. Dataverse can also be defined as an API, everything that we perform in Dataverse is creating an API, and these are the same APIs that we can consume in Power Platform services but also custom applications (like those made in Visual Studio).
There are possibilities for adding business rules that can define the specifics of data storage and trigger new actions and instances within the Dataverse and Power Automate. Also, many apps and Poer BI reports can be connected with one Dataverse.
Below API, we have a security layer side of Dataverse. Dataverse knobs authentication with Azure Active Directory (Azure AD) to allow conditional access and MFA. This ensures that only authorised personnel can see the data. Dataverse supports table and column-level authorisation and robust auditing abilities.
Beyond the security layer, we have the logic layer, which can be applied to the data level. For all the users, the same rules (related to duplicate detection, business rules, workflows etc.) are applied irrespective of how they interact with the data.
Now the heart of Dataverse – the Data- gives a way to structure our complex business data with low-code methodology. Here discover, model, validate, and report on your data. This control ensures your data looks how you want, regardless of how it is used.
The next is the Storage: Dataverse is a relational database, and all the physical data in Dataverse is stored in the Azure cloud – so you do not worry about the handler.
The last layer is Integration – Dataverse offers a rich integration layer where we can seamlessly interact with other systems. This can be achieved using APIs, webhooks, eventing, and data exports, giving you the flexibility to get data in and out.
Note: The amount of data available in your instance of Microsoft Dataverse is based upon the number and type of licenses associated with it.
A Dataverse database is a single instance of Microsoft Dataverse that stores data in a set of standard and custom data structures called tables and supports large data sets and complex data models.
The standard table design in a Microsoft Dataverse database is based upon an open data model standard called Common Data Model. The structure of a Microsoft Dataverse database is based on the definitions and schema in the Common Data Model. The key benefit of using the Common Data Model as the basis of a Microsoft Dataverse database is the simplified integration of any solutions that use a Common Data Model schema because the standard tables of the solution are the same.
Digest 2 scoops of Dataverse and get ready to taste the Third Scoop!
