Hyperscale Your Enterprise Business Applications with Microsoft Dataverse

Over the past three years, the annual growth rate of enterprise data within Fortune 500 companies has been remarkable, driven by an exponential increase in data generation and the strategic imperative to leverage data analytics. The volume of data continues to grow as enterprises build and deploy new applications within their organizations. IDC has predicted that 1 billion applications will be built over the next 4 years, each of which will generate data that must be ingested, transformed, activated, and managed. 

The accelerating growth in data volume, coupled with its siloed nature, makes deriving insights costly and time-consuming. As a result, enterprises must improve data access to drive productivity and efficiency across different business teams. However, they face seemingly insurmountable hurdles when their data is contained in disparate sources. Beyond the inherent challenges posed by data silos, every enterprise is acutely aware of the security risks it faces due to the rise of active targeting by global threat actors, making security a non-negotiable priority. IT must safeguard data while enabling the enterprise to manage it at scale without redundancy or increased costs. 

Recent technological advancements in AI and machine learning, including data-grounded Copilots and context-rich analytical and recommendation systems, present enterprises with new ways to manage their data estates at scale using Microsoft Dataverse and deliver generative AI solutions with this knowledge using Microsoft Copilot Studio.  

Microsoft Dataverse offers a comprehensive solution by empowering low-code makers to accomplish more, while providing pro developers and IT teams with enhanced power and scope. This enables enterprises to unlock greater value from their data, while ensuring cost-efficiency, security, governance, and compliance across the entire application data lifecycle. 

With applications built on Dataverse, enterprises can improve productivity at every phase of the data lifecycle. Dataverse provides: 

• Seamless ingestion of data with AI-assisted mapping; 

• Support for large-scale business needs with highly performant and scalable APIs and Power Platform connectors; 

• Business insights with support for Direct Querying using SqlQueries (using Tabular Data Stream (TDS)), Power BI capabilities and built-in Microsoft Fabric link capabilities;  

• Storage capacity tools to manage data at scale; and 

• The enterprise-grade security of Microsoft Entra ID. 

With the ever-growing volume of data generated by enterprises, it is critical that organizations find ways to ingest data at scale – but ingestion is only the first step in the process. Features like AI assisted mapping can provide meaningful productivity gains through recommendations on Dataverse table selection for new data ingestion. Time spent on schema analysis and data ingestion can be further minimized by leveraging Power Platform dataflows: a self-service, cloud-based data preparation technology designed to simplify and accelerate these processes. 

AI-Assisted Dataflows enable enterprises to efficiently ingest, transform, and load data into Power Platform environments with greater precision and less guesswork. For instance, Dataverse’s AI-assisted mapping suggests column mappings when importing data into Dataverse tables. By leveraging these AI-driven recommendations, makers can effectively reuse the robust data schemas already in place within business applications, eliminating the need for manual data remapping. This not only improves data quality and consistency, but also enhances overall productivity. Additionally, solution-aware dataflows support the seamless migration of apps and components across environments, (such as from test to production,) addressing a critical IT requirement. 

When data migration is not the preferred solution due to challenges associated with managing large volumes of data across different IT systems, Dataverse virtual tables provide IT teams with the ability to access data from non-Dataverse sources in real-time. Virtual tables provide read/write access to enterprise data without the need for ingestion into Dataverse. This capability creates a low-code pathway for enterprises to modernize legacy applications, enabling the development of automated flows, interactive Power Pages, and AI-driven knowledge bases, while avoiding the complexities of data replication and reducing the impact of API thresholds, throttling, and costs on invoking APIs. 

By leveraging virtual tables, enterprises can create relationships between external data and data that exists natively in Dataverse. Once these connections are established, data can be seamlessly accessed from multiple data silos across the enterprise, enabling makers to effectively utilize this data in the applications they’re building. Learn more about creating virtual table relationships. 

Enrich your data using new AI Functions  

Valuable enterprise data often languishes in an unstructured format. For example, an un-alerted comment field may contain key feedback that has the potential to dramatically improve customer satisfaction. AI functions help enterprises summarize, translate, and extract nuggets of insight from this data, which may otherwise go untapped, using prompts. To drive action, the business can even utilize AI to craft customer emails and documents, adding significant value and increasing productivity.  

While AI Functions provide powerful out-of-the-box capabilities, enterprises can take AI integrations even further by grounding custom AI prompts with Dataverse data. 

This allows the enterprise to: 

• Link AI prompts directly to business data in Dataverse tables; 

• Provide context-specific responses based on the organization’s information; and 

• Improve accuracy by referencing up-to-date data from the internal environment. 

For example, an enterprise could create a custom prompt to extract key details from customer proposals, grounded in its Proposals table in Dataverse. This combines the power of large language models with proprietary business data. 

Support your business needs for large volume operations

In today’s world, increasingly driven by data and AI, Dataverse Elastic Tables backed by Azure Cosmos DB is a powerful option with practically unlimited storage. Makers can bulk load large data volumes at high throughput and enable applications to scale up to 120 million writes per hour and 6000 reads per second, while storing 3 billion records in a single table, all with low code. Elastic Tables even supports business scenarios that require flexible schemas with JSON payload, and is already being used extensively by Microsoft Dynamics 365 applications. It allows enterprises to optimize data capacity utilization with its auto delete capability based on time to live functionality – and as always, data is protected by Dataverse security. Learn more about Dataverse Elastic Tables. 

With rapid business growth inevitably leading to large data volumes in existing standard Dataverse tables (which supports up to 100TB), enterprises need the ability to hyperscale write operations. Dataverse bulk operation APIs  are designed for enterprise makers to support these high throughputs write scenarios. Bulk operation APIs like CreateMultiple, UpdateMultiple, and UpsertMultiple can provide throughput improvement of up to 5x, growing from 2 million records created per hour using ExecuteMultiple to the creation of 10 million records in less than an hour. Customers have saved up to 82% of the time spent in end-to-end scenarios using CreateMultiple, UpdateMultiple, and UpsertMultiple in Dataverse SQL tables. 

Drive action on your insights with Fabric from Dataverse 

Dataverse makes hyperscale data accessible and understandable, identifying insights and improving business outcomes. With Microsoft Dataverse Link to Fabric, enterprise data stays in Dataverse, without data copy, while authorized users work with it in Fabric and Power BI to unlock new insights. Using Fabric tools such as SQL, Spark, and dataflows, enterprises can combine, transform and aggregate additional enterprise data into their Dataverse data, enabling near real time insights. 

Enterprises often need to leverage data across different lines of business (LOB) beyond Dataverse applications. Fabric mirroring makes it easy to move this enterprise data into Fabric, where Fabric tools generate insights by combining the enterprise LOB data with the Dataverse data already linked to Fabric. 

When a business scenario requires LOB or other IT data (such as Azure SQL Database, Azure Cosmos Database, and Snowflake) to be maximized from within a Dataverse application to drive business outcomes, low code makers can create Dataverse virtual tables for all the data sitting in Fabric and leverage Power Apps within the Dataverse application. 

“To quickly answer questions, a client’s Accounts Receivable (AR) team will often desire historical sales invoice details in their Dynamics 365 Financials application, but this data could be in multiple systems and oftentimes is cost prohibitive to migrate into a central ERP.  Now with Fabric-based virtual tables, we will implement a Dynamics 365-embedded Power App sourced from legacy sales data housed in a Fabric data warehouse. We love it…same data, same answer, and delivered in less time!” 

Travis Christens, Director Business Analytics and Azure –armanino

Data capacity management 

With rapid enterprise digitization and business expansion resulting in exponential data growth, further accentuated by the prevalence of AI, enterprises need to ensure continued performance of the live application and optimize storage capacity consumption. This must be achieved while ensuring adherence to compliance and regulatory requirements, by reducing the risks associated with historical data. Dataverse tools such as Power Platform capacity reports assist organizations to better manage application data by providing visibility into the storage capacity consumed by business applications. IT admins can further reduce unnecessary storage consumption with regular scheduled usage of Bulk Delete.  

In many business scenarios (such as customer service case management, Finance Ledger, and Supply Chain Inventory), even as the data lifecycle of the business application moves from active to inactive over a defined period, inactive data must be retained for at least seven years for legal and regulatory compliance. While Dataverse has no set limit on active data required to support an enterprise’s unlimited business growth, database capacity consumption can be reduced by storing historical inactive data in Dataverse long term retention for Dataverse and Dynamics 365 Finance and Operations applications. 

Dataverse enables an enterprise grade security model for modern access requirements  

In today’s business environment, teams need to share and collaborate on data spread across multiple resources. Historically, enterprises have been forced to choose between fostering efficient, productive work and ensuring the security, governance, and regulatory compliance of their data and IT systems.  

Dataverse enables a more efficient business model by allowing data access for multiple users across different teams while providing enterprise-grade security backed by Microsoft Entra ID. Enterprises with matrix-based organizational structures can now enable users to own records across different business units, granting each user access control and deletion privileges for the specific records they own – thereby improving productivity. For example, an enterprise’s customer service associates can be granted access to customer accounts and emails by the sales team without violating access controls. 

Security is a huge concern for every organization, and Dataverse offers capabilities such as customer managed key, customer lockbox, environments security groups, Dataverse Audit, and Azure vNet to ensure enterprises can be confident that their data is secure both at rest and in transit. The Power Platform security hub allows administrators to assess the security posture for the tenant, identify and act on recommendations, and use its rich set of high value tools to gain visibility, detect threats, and proactively set policies in place to safeguard from vulnerabilities and risks. 

Next Steps 

In summary, Microsoft Dataverse provides a powerful and scalable solution for enterprises seeking to manage their data efficiently and securely, empowering organizations to overcome the challenges of data silos, enhance productivity, and ensure compliance with security standards. Features such as AI-assisted mapping, virtual tables, and Elastic Tables enable businesses to ingest, transform, and activate data seamlessly, supporting large-scale operations without the need for extensive data migration. Moreover, Dataverse’s integration with Microsoft Fabric and its security features backed by Microsoft Entra ID ensure that enterprises can manage their data lifecycle effectively from ingestion to long-term retention, while maintaining robust security and governance. This comprehensive approach allows enterprises to unlock the full potential of their data, driving actionable insights and improving business outcomes. 

As the volume of enterprise data continues to grow, adopting a solution like Microsoft Dataverse becomes increasingly critical. It not only addresses the immediate needs of data management, but also positions businesses for future growth and innovation. Enterprises are encouraged to explore the capabilities of Dataverse to enhance their data strategies and achieve greater efficiency and security in their operations. To fully unlock the potential of your data and take your organization’s data strategy to the next level, consider diving deeper into the specific capabilities that Dataverse provides. 

AI-Assisted Mapping: Streamline your data ingestion processes and improve data consistency by leveraging AI-driven recommendations for seamless integration. 

Modernized Business Units: Empower your teams to collaborate effectively across different business units with enhanced data ownership and access control features. 

AI Functions: Harness the power of AI to derive actionable insights from your data, transforming it into a strategic asset. 

Elastic Tables: Support large-scale operations with the flexibility and scalability that Elastic Tables provides, ensuring your data infrastructure grows with your business needs. 

Fabric Link: Integrate Dataverse with Microsoft Fabric to enable seamless data flows across your organization, driving efficient data activation and business outcomes. 

Long-Term Data Retention: Implement robust data lifecycle management strategies with Dataverse’s long-term retention capabilities, ensuring compliance and governance over time. 

To learn more about managing security and governance within the Power Platform, visit Power Platform Security Hub on Microsoft Learn. 

By taking these next steps you’ll be well on your way to optimizing your data management strategy, enhancing productivity, and ensuring the security and compliance of your enterprise’s data. Explore these features today and see how Microsoft Dataverse can help you achieve your business objectives.