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.
Need for Dataverse
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.
Microsoft Dataverse is the one-stop destination for harnessing a broad variety of data being generated across different domains throughout the globe. It provides a flexible, scalable, and secure SaaS platform for thorough data handling. Moreover, its simplistic UI renders it extremely easy to leverage and integrate with other data platforms and solutions like Power.
Why Use Dataverse?
All data types supported
Microsoft Dataverse supports all kinds of data, from files, images, blobs to relational databases and data lakes. Dataverse comes with a pile of enterprise-ready services like table automation, and multi-platform integration that facilitate its purpose.
App Integration
Dataverse is often integrated with other Microsoft technologies like Power Apps for workflow automation. This is extremely useful if the data collected and analyzed in Dataverse shall be used to drive certain enterprise pipelines. Dataverse is already integrated with prominent Microsoft solutions like Dynamics 365, MS Excel, Power BI, Azure Data Factory, etc. However, it also provides a REST API, developer SDK, and a bot-based app alternative for increased functionality.
Security and Compliance
Microsoft Dataverse is built on Azure and leverages Azure’s authentication and security features like Active Directory for encryption and authenticated access. It divides data access on the basis of two models: manager and position. The security features also permit row-level and column-level sharing.
Microsoft Dataverse is a trusted SaaS data platform. All the concerned data adheres to regulatory compliances and is validated by audits and certifications.
Dataverse Databases
Dataverse is known for creating standardized databases which further contain tables. A Dataverse database is a cloud-based unit instance that stores data in standardized structures called tables. A table is a collection of multiple rows containing both standard and custom data. Logical columns help in handling specific aspects of the data in the rows. Multiple database instances can be created in Dataverse to store business data. Tables are extendable and customizable to adhere to business needs. These integrated business solutions can be shared with multiple partner organizations for collaborative data analysis.
Dataverse databases can support complicated data models. Tables can hold millions of items, and storage in each instance of a Microsoft Dataverse database can be extended to about 4 TBs of data, per instance(1TB=1024GB). The amount of data that is available in an instance of Dataverse is based upon the number and types of licenses the data-handlers have been issued with. Data storage is mutually pooled by all the license holders and can be shared. However, in case of an outage, additional resources could be purchased accordingly.
There are two main categories of tables.
1. Standard- Standard tables have a pre-defined layout and structure. They are created for every instance of Dataverse databases. More columns could be added to any standard table, but columns could be deleted only from custom tables.
2. Complex– Complex tables have complex workflows and pipelines, and intricate server-side business logic.
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.
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.
There are two main types of relationships.
1. One-to-Many Relationships: A one-to-many relationship refers to the parent-child cardinality between two tables. Let us take an example of 2 tables, A and B. In our example, an element of A may have connections with many elements of B. However, a given element of B is linked to only one element of A. A can be considered to be a parent table and B can be the child table. This would imply that while A can have multiple children, B can have only one biological father/mother.
2. Many-to-Many Relationships: This cardinality can be established between two tables A and B, wherein multiple elements of A can be connected with multiple elements of B, and vice-versa. A valid example of this could be the relationship between customers and the products purchased. One customer could purchase multiple products and one class of products ( for eg: Geeksforgeeks DSA course) could be purchased by multiple customers.
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.
It is important to note that these resources could be only be configured and utilized within the given environment by authenticated users. Environments are bound to geographical locations and databases are created in the data-centers corresponding to those geographical locations. More than one environment could be created for separate workflows like development, testing, and production.
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.
- Dataverse, in itself, is not a database. Therefore, some Azure database services like CosmosDB would need to be integrated with it. If you do not wish to include the database, Dataverse would be rendered inefficient.
- There is always some limit to storage capacity in Dataverse when it is integrated with third-party services like Microsoft Teams.
- Premium and Licensing featured are costly, and could not be used if the user is on a budget.
Under these situations, other Microsoft services like Power BI could be leveraged. However, Dataverse has a diverse set of advantages and its integration is definitely a boon.
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