Fusion Data Intelligence Propels Oracle to Full-stack Cloud Provider

TBR Perspective

TBR joined industry analysts at Oracle’s (NYSE: ORCL) former headquarters in Redwood City, Calif., for the one-day Oracle Analytics & AI Summit, which centered on trends, advancements and use cases in the world of analytics and generative AI (GenAI). While we did not shatter any course records on the Oracle Red Bull Racing simulator, we did grasp how Oracle is addressing one of the top trends we see in the market: Cloud computing has become table stakes in digital transformation, and customers are shifting their focus to the data and how it can be translated into actionable insights.


In five years, Oracle has consolidated Oracle Analytics Cloud (OAC) and launched prebuilt cloud-native analytics solutions for each of its four Fusion apps suites. Oracle is now embarking on a new frontier with Fusion Data Intelligence (FDI), the intelligent analytics layer that will fuse Oracle’s roles as both a SaaS and IaaS provider in the race for GenAI workloads.

New Intelligent Data Layer Elevates Oracle’s Role as Full-stack Cloud Provider

At TBR, we often talk about how Oracle uniquely serves the entire cloud stack at scale with infrastructure, platform services and applications. With its strengths solidified in database and back-office apps, the rapid emergence of Oracle Cloud Infrastructure (OCI) is rounding out Oracle’s full-stack narrative, driving a greater level of stickiness with customers looking to consolidate point solutions and potentially reduce costs.


But we are seeing an inflection point in the market. Cloud computing has become a standard component to digital transformation in some capacity, and buyers are shifting their focus to the data; specifically, how they can access and integrate cross-departmental data to capitalize on GenAI and streamline their business.


With finance, sales and HR data already sitting in Fusion applications — which are native to OCI — and an OCI lakehouse architecture built on trusted database services (e.g., Exadata, MySQL Heatwave), Oracle has a unique ability to build out an intelligent data analytics layer that cements Oracle’s role as both an IaaS and SaaS provider. We are seeing this firsthand with FDI.


Announced at Oracle Cloud World 2023, FDI marks a shift in the Oracle Analytics strategy to focus less on addressing one-and-done tasks but more on making analytics part of an ongoing, integrated process with additional AI models. For instance, FDI still draws on the platform foundation of OAC and the four Fusion Analytics modules (ERP, Supply Chain Management [SCM], Human Capital Management [HCM] and Customer Experience [CX]) but also incorporates new prebuilt models for predictive and prescriptive insights within those Fusion applications. For example, in Fusion HCM, these models might support analytics use cases for continuous listening, diversity analysis and employee skill matching.

Because of Fusion Applications, Oracle Analytics Can Close the Loop on Business Processes

With the Fusion applications suite, Oracle Analytics has always had a unique ability to engage with HR, finance and supply chain leaders directly within their workflow to solve a unique problem. We expect FDI will fast-track adoption of analytics among Fusion customers by allowing them to run Fusion data pipelines uninterrupted with each software update and then perform tasks like snapshots and KPIs on that data as part of a single SKU.


This is particularly true of customers that want to focus less on DevOps and more on analytics but also want to close the loop on an entire business process. One compelling example was a theoretical healthcare organization using FDI to not only understand why vaccination rates are down but also connect to Fusion HCM to see if there are enough staff on hand to launch a new program, and schedule accordingly. FDI already exists today for Oracle Health and is one of the key value propositions behind the Cerner acquisition.

AI Enhances OAC’s Value for Both Customers and Partners

Oracle has a rich history of embedding AI into its products, and the company’s approach to GenAI is no different. With support for the OCI GenAI service in OAC, the core component of FDI, Oracle is enabling self-service analytics with features like natural language queries that help analysts contextualize and interpret data.


One of the more interesting features we experienced through an OAC demo was the use of AI-based avatars. Oracle is working with Synthesia, a third-party firm, to pull data from OAC and have different avatars tell stories around that data for specific clients. In addition to watching live demos, we also heard directly from customers in industries like healthcare, transportation and technology on how they are using OAC. As is true for many Oracle solutions, the primary adoption driver for OAC was standardization and the ability to consolidate disparate tools like Power BI (business intelligence) and Tableau on a single platform that can be scaled to different personas throughout the organization.


We also heard from both Tier 1 and Tier 2 professional services partners that are driving SI business by migrating customers from the legacy Oracle BI stack to OAC and, increasingly, selling FDI as part of broader app transformation engagements. If the global system integrators (GSIs) want to drive high-margin consulting services around GenAI, we believe they need to account for an intermediary layer that bridges the gap between cloud infrastructure and the back, middle and front office. FDI serves this purpose. Since for most customers analytics will almost always be the end state, GSIs have an opportunity to work backward from FDI into key workloads, including data lakes and ERP systems as part of a client’s cloud transformation, supplemented by their own IP.

OCI GenAI Service Hits the Market

At the start of this year, the OCI GenAI service became generally available, officially marking Oracle’s entry into a budding market. With general availability, Oracle extended support for large language models (LLMs) beyond Cohere, including Meta’s (Nasdaq: META) Llama, as part of the notion that customers should be able to use different models that can be tweaked with their own data, according to use case.


Meanwhile, capabilities like OCI AI Agents — which enable RAG (retrieval augmented generation) — and AI Quick Actions within OCI Data Science, also support specific use cases by helping customers contextualize data and access third-party LLMs. On their own, these capabilities do not necessarily differentiate Oracle from what other hyperscale clouds are delivering — although Oracle was smart to cozy up to NVIDIA (Nasdaq: NVDA) for GPUs early on — but the ability to power the same analytics and apps stack with the OCI GenAI service is unique. As we have long said, differentiation in GenAI will not come from the models themselves but rather from the data that feeds into them and ultimately connects customers to solutions and use cases.


As such, successful vendors will take a measured approach and will need to partner with GSI peers to address data literacy challenges and apply model governance. FDI’s ability to collect data from Fusion applications and deliver a unified data model that can establish a governance framework and help train nontechnical personas speaks to the elevated role of Oracle Analytics in not only capturing GenAI workloads but also executing on the full-stack narrative throughout the broader Oracle organization.