In this guest blog post, Mitesh Shah, Director of Cloud Product Management, GTM, Alliances at Denodo Technologies, explains how the Denodo Platform along with Microsoft Fabric enables a robust data integration, data management, and data delivery platform in hybrid and multi-cloud environments. Learn how you can extend your data analytics and generative AI use cases and deliver smart data management in real time.

Data landscape and business challenge
Enterprises deal with massive amounts of data that have become the backbone for advanced analytics and generative AI projects. As the data volume continues to grow, it is often fragmented and siloed across multiple data sources, waiting to be analyzed. At the same time, the emergence of large language models (LLMs) and generative AI mark a significant leap in technology, promising to deliver transformational automation and innovation across diverse industries and use cases.

The most common challenge in enterprise data management is multiple lines of businesses operating silos of data that are not truly connected. It is difficult to find deep and accurate insights without a single source of truth. Stitching together unique analytics tools across organizations is complicated. Costs associated with procuring and managing these capabilities can be exorbitant. And there is a significant risk associated with lack of governance.

At the same time, generative AI relies on LLMs, which have inherent limitations around their training data. These LLMs lack insights about enterprise-wide data, thus limiting operational use cases tied to real-time reporting and decision making. This impacts generative AI-led data management because of inaccurate and inconsistent results from LLMs. The results are end-user mistrust, regulatory violations around ethical use of AI, and issues with security and privacy compliance in the data management landscape.

The Denodo Platform and Microsoft Fabric to the rescue
Most enterprises have established a centralized data and analytics (D&A) center of excellence to support federated D&A initiatives and prevent enterprise failure. Data is a critical component of these D&A centers, which have become a key priority for organizations.

Supporting well-known corporate architectures such as data fabric and data mesh, the Denodo Platform, available in the Microsoft Azure Marketplace, offers a robust framework and provides a semantic layer for data management, abstracting data from end users while democratizing access across multiple tools and services. In a similar fashion, Microsoft Fabric brings together the best parts of data mesh and data fabric to provide a one-stop shop for data integration, data engineering, real-time analytics, data science, and business intelligence needs without compromising data privacy and security.

Microsoft Fabric combines Azure Data Factory, Azure Synapse Analytics, Data Explorer, and Power BI into a unified experience in the cloud. The open and governed data lakehouse foundation provides a cost-effective and performance-optimized fabric for business intelligence, machine learning, and AI workloads at any scale. It is the foundation for migrating and modernizing existing analytics solutions, whether this be data appliances or traditional data warehouses.

This architecture may work with a few use cases limited to all data being centrally stored in OneLake. However, it is not a common scenario as users deal with various formats of data across various applications including SaaS (such as Salesforce, ServiceNow), on-premises and legacy applications, and data spread across multiple regions. The Denodo Platform extends use cases by providing a strong integrated framework across all sources of data in hybrid and multi-cloud environments.

A unified data access layer has always been critical to delivering business insights and driving business success. But next-generation AI applications will make it even more important for organizations to take full advantage of the data at their disposal, regardless of where it is stored and what form it takes. As LLMs and generative AI technology inevitably evolve, organizations will also require a data management foundation that is flexible and agile, allowing new data sources to be added quickly and new data views to be developed easily to support new emerging AI use cases. An adaptable data management layer also maximizes the ability to interchange off-the-shelf AI services as newer, better, and cheaper options are released.

Key strengths and features of the Denodo Platform
There are a variety of use case scenarios where the Denodo Platform adds value by augmenting and complementing the strengths of Microsoft Fabric architecture:

Customers who don’t want to migrate all their data into OneLake. This is a common and practical scenario with data management
Users looking for unified data security across all data repositories and environments, outside of OneLake
Flexible deployment options in a hybrid and multi-cloud environment, supporting data modeling and query optimization techniques to accelerate data integration and delivery in a performant manner
Ability to model data to business users and accelerate cloud adoption via transition of workloads to Azure at their own pace without impacting the data consumers

Benefits of integrated technologies
The Denodo Platform, leveraging data virtualization technology, minimizes the need for costly data movement or consolidation before augmenting an AI application. Here are a few common use cases and benefits delivered via the Denodo Platform and Microsoft Fabric:

Data self-service for data democratization in a hybrid and multi-cloud environment (examples: self-service reporting and KPI dashboards, data mesh/self-service data product development)
IT infrastructure modernization (fueling cloud workload transition from on-premises to cloud, legacy retirements, application consolidations, and data lake optimizations)
Data foundation for improved customer experience (driven via generative AI support for Customer 360, self-service portals, digital engagement applications, full-journey reporting, and analytics)
Improve operational efficiency, agility, resilience (examples: Data-as-a-Service/data marketplaces, and supply chain optimization)
Centralized governance, risk, compliance (examples: centralized data privacy/security for all sources beyond OneLake, financial regulatory reporting, sustainability/ESG reporting, anti-fraud/money laundering, and risk analytics)

The Denodo Platform provides a consolidated data foundation for AI applications to access integrated data and offers other key benefits, including:

A unified, secure access point for LLMs to interact with and query all enterprise data (ERP, operational data mart, EDW, application APIs)
A rich semantic layer, providing LLMs with the needed business context and knowledge (such as table descriptions, business definitions, categories/tags, and sample values)
Quick delivery of logical data views that are decoupled and abstracted from the underlying technical data views (which can be difficult to use by LLMs) 
Delivery of LLM-friendly wide logical table views and built-in query optimization relieves LLMs from dealing with specific data source constraints or optimized join strategies

In summary, the Denodo Platform’s ability to manage and process widespread corporate data (structured and unstructured) alongside Microsoft Fabric support via OneLake creates a strong foundation for supporting generative AI applications. This enables real-time data access for chatbots needing data from various systems to deliver accurate and appropriate responses to customer prompts. The Denodo Platform and Microsoft Fabric deliver a unified data fabric for a strong and governed data foundation in a multi-cloud environment, thus accelerating retrieval augmented generative AI projects and amplifying generative AI applications to deliver business value across the enterprise.

You can experience all these capabilities via Denodo Enterprise Plus, available in the Microsoft Azure Marketplace.

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