In the previous post, we traced how Fusion Data Intelligence (FDI) evolved from OBIA. In this second instalment of our FDI‑introductory series, you’ll explore the underlying technology and architecture that power FDI’s cloud-native analytics platform.

2. The FDI Architecture Ecosystem (The “Big Picture”)

At its core, Fusion  Data  Intelligence (FDI) is a fully managed, cloud-native analytics platform running on Oracle Cloud Infrastructure (OCI). It stitches together your Fusion Cloud Applications, Oracle-managed data pipelines, Autonomous Data Warehouse (ADW), and Oracle Analytics Cloud (OAC) into a seamless, scalable end-to-end analytics solution - one that Oracle deploys, operates, and continuously evolves for you (there is some configuration that administrators need to carry out).

First, Fusion Cloud SaaS applications - including ERP, HCM, SCM and CX pillars - serve as the transactional data sources. Oracle provides prebuilt ingestion pipelines tailored to each functional Pillar, handling everything from data extraction and change data capture (CDC) to transformation and consistent mapping into analytics-ready format .

These pipelines write data directly into an OCI-hosted Autonomous Data Warehouse, which transform and load the Fusion data into a unified star-schema data model covering multiple functional domains. The schema is:

• Immutable and prebuilt, reducing modelling effort,
• Extensible, allowing for additional external or custom Fusion data,
• Optimised for high-performance querying across SaaS application pillars via Conformed Dimensions like customer, product, ledger and fiscal calendar .

This architecture supports refreshes that can be scheduled incrementally or on demand, with zero downtime - ensuring analytics remains uninterrupted during data pipeline updates. Custom flexfield extensions from Fusion Applications can be included in the pipelines, bringing bespoke business data into the analytics layer.

Once data arrives in the Autonomous Data Warehouse (ADW), Oracle Analytics Cloud takes over for semantic modelling and visualisation. A prebuilt semantic layer wraps the raw star schema into business-friendly subject-area views - covering finance, human resources, supply chain and customer experience - complete with standardised key metrics and dashboards .

Through OAC, FDI delivers not just dashboards but intelligent, action-driven analytics, featuring natural-language querying, ML-based forecasting and anomaly detection to name just a few.

🔗 Summary Flow

1. Fusion SaaS Apps (ERP/HCM/SCM/CX) →
2. Oracle-managed data ingestion pipelines (CDC, ETL, flexfield support) →
3. Star-schema data model in Autonomous Data Warehouse (extensible star schema, conformed dimensions) →
4. Oracle Analytics Cloud (semantic layer, dashboards, AI powered insights and intelligent apps).

This end-to-end ecosystem is fully managed by Oracle - covering provisioning, upgrades, performance tuning, and integration with Fusion App releases - offering a friction-free, scalable approach to enterprise analytics (there is some configuration that needs to be done by administrators).

3. Data Movement & Integration

​​FDI’s data movement layer is built around Oracle-managed, prebuilt pipelines that automate ELT and Change Data Capture (CDC) for Fusion Applications (ERP, HCM, SCM, CX). These pipelines are configured and controlled through the intuitive FDI Console, making it easy for administrators to activate, modify or schedule updates with minimal effort. You don’t need to build complex ETL processes - Oracle handles the heavy lifting, while you focus on business relevance and reporting needs .

By default, data pipelines are incremental with zero downtime, keeping analytics up-to-date without interrupting service. You also have the flexibility to perform on-demand full reloads, useful for data corrections or model updates - all managed with just a few clicks in the Console .

Crucially, the architecture supports extensibility in two key ways:
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1. Fusion data flexibility – Custom flexfields defined in Fusion Apps are automatically picked up and mapped into the ADW schema without additional development .
2. External data ingestion – You can supplement your analytics with data from outside Oracle, using FDI Console’s data augmentation connectors (e.g. Salesforce, EBS, PeopleSoft, Shopify), self-service file uploads (Excel), direct ETL tools like Oracle Data Integrator, Oracle Integration Cloud or your choice of third-party loaders to a custom schema in the same ADW instance. For bulk external loads, FDI supports bulk data augmentation jobs that can be scheduled and monitored via the Console UI .

All pipelines and augmentations are managed through the FDI Console. As an administrator, you can configure initial parameters - such as extract start dates, currency preferences, and schedule frequency - directly in the console interface. Any subsequent edits to pipelines, functional areas, or augmentations are seamless, with Oracle handling deployment and execution behind the scenes

4. Lakehouse & Warehousing Foundation

At the heart of Fusion Data Intelligence lies a star-schema model deployed on Oracle’s Autonomous Data Warehouse (ADW) - a cloud-native, self-tuning database that underpins fast, enterprise-grade reporting and analytics. Here’s how it’s structured and why it matters:

⚙️ Prebuilt Star Schema in ADW
When FDI is provisioned, Oracle automatically creates a prebuilt star schema in ADW. This schema includes fact tables and a network of conformed dimensions - shared across multiple functional areas - that serve as the glue for cross-pillar analytics.

Common dimensions include:

• Customer / Common Party – used across AR, AP, SCM and CX for a 360° view of customer interactions 
• Supplier – central to procurement and payables
• Product – essential for SCM, finance, and sales analysis
• Fiscal Calendar – shared across financial, HCM, project and supply chain modules
• Business Unit / Ledger – enabling segmentation and consolidated reporting

These shared dimensions enable users to analyse, for example, how procurement spend (SCM) impacts cash flow (finance), or how HR-driven workforce changes correlate with sales performance - a cross-functional insight made possible by a common semantic backbone.

🏗️ Support for External Data & Custom Schemas

​FDI doesn’t just ingest Fusion source data - it enables easy integration of external datasets into the same ADW environment. Whether it’s non-Oracle systems, legacy data, purchased data feeds, or even weather information, FDI supports loading external tables into custom schemas that can extend the star schema and semantic model.

This extensibility is key to bridging out-of-the-box analytics with bespoke business insights - enhancing customer segmentation, supplying additional cost drivers to per-product profitability, or blending external KPIs directly alongside Fusion metrics.

🔍 Benefits of the Lakehouse Foundation

1. Cross-pillar consistency: Reporting across HR, finance, supply chain and CX benefits from shared dimensions and semantic logic.
2. Query performance: ADW’s columnar, parallel engine delivers high performance on aggregated workloads across large datasets.
3. Scalability & elasticity: Cloud-native scaling ensures performance keeps pace with data growth—without manual tuning.
4. Governance in one place: Shared data model and schema simplify security, data lineage and audit tracking.

✅ Summary
Under the hood, FDI’s star-schema in ADW provides a robust, extensible greenfield analytics foundation. Built on conformed dimensions and a scalable data warehouse, it enables seamless mash-ups of Fusion data with external sources, supporting rich, multi-domain analytics that truly span the enterprise.

5. Semantic Layer & Pre‑Built Metrics

FDI abstracts hundreds of physical tables into logical business subject areas - finance (GL profitability, AP ageing, AR revenue, Trial Balance), HCM (talent acquisition, workforce core), procurement (spend, POs), and CX (campaign ROI, opportunity pipeline) - all underpinned by conformed dimensions. It includes a KPI library with over 2,000 standard metrics, accessible via Oracle Analytics Cloud’s intuitive key-metric editor and drag‑and‑drop visualisations. In essence, this semantic layer creates a unified business vocabulary that simplifies reporting and ensures consistency across the enterprise  .

🔐 Complimenting Fusion-Defined Security

FDI leverages Fusion’s built-in role-based security model, so the semantic layer inherits data roles, duty roles, and row/object-level filters defined in Fusion Cloud Applications. Access control is enforced through the Oracle Identity and Access Management (IAM) Service and the FDI Console, ensuring that users only see data they’re authorised to view. This unified approach simplifies administration and compliance by avoiding double entry of security definitions  .

🧩 Hiding Complexity Through Logical Abstraction

Rather than exposing raw tables, FDI offers a logical semantic layer that shields users from underlying complexity. Here’s what it achieves:

• Simplified reporting — Subject-area views like “GL Profitability” or “Spend by Supplier” present meaningful business concepts, not table joins.
• Consistent vocabulary — Terms like “Customer”, “Supplier” or “Fiscal Calendar” remain consistent across pillars and dashboards.
• Reusability — Prebuilt key metrics can be used across workbooks and dashboards without redefinition.
• Governed extensibility — Analysts can add custom dimensions or metrics without touching base tables, via semantic extensions that maintain upgrade compatibility  .

✅ Summary: User Experience & Governance Wins

7. Governance, Security & Lineage

Fusion Data Intelligence isn’t just about delivering insights - it’s built on a robust foundation of security governance and data lineage that brings trust, safety, and compliance to the analytics lifecycle.

🔐 Security Inherited from Fusion & Managed via OCI IAM
FDI inherits its security framework directly from Fusion Cloud Applications. Role-based access, including data roles and duty roles configured in Fusion, are seamlessly enforced within the FDI semantic layer and Autonomous Data Warehouse (ADW). This ensures that users can access only the data they are authorised to see - without duplicating access definitions in multiple systems.

User and group management within FDI is handled through OCI’s Identity and Access Management Service (IAM). You can sync your Fusion App users and roles into OCI IAM or manage them natively via OCI, and then assign access through system and job-specific groups tailored to FDI. This 1:1 mapping ensures governance is inherited and consistent across both transactional and analytics layers.

Oracle also manages infrastructure-level security - covering upgrades, patching, encryption, IAM policy enforcement, key management, and auditing - helping to maintain compliance and relieve the operational burden on your team. 

🧭 Data Lineage & Quality Built-In

​Trusted analytics demand transparency - and FDI delivers that through built-in data lineage and validation mechanisms. The system tracks the flow of data from source tables in Fusion Apps, through ingestion pipelines, into curated star schemas, and finally into Semantic Layer metrics and dashboards.

Fusion SCM Analytics documentation provides end‑to‑end lineage spreadsheets that detail column‑ and table-level mappings, making it easy to trace every KPI back to its source fields. You can also monitor pipeline activity in the FDI Console, which records execution timestamps, row counts, and error logs - providing a clear audit trail of data loads and transformations.

Further, FDI includes validation metrics that reconcile data loaded into ADW against transactional data in Fusion. These can be scheduled or run on‑demand, with reports surfaced directly in OAC - making it easy to identify data drift or discrepancies and swiftly pinpoint areas for correction
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✅ Summary: Trust, Safety, and Compliance

8. Why This Architecture Matters for Organisations 🚀
Fusion Data Intelligence goes far beyond traditional BI. It sits at the heart of Oracle’s broader Data Intelligence Platform, delivering a unified, 360° view across all enterprise data—transactional, analytical, structured, and unstructured  .

🌟 A Unified Data-Intelligence Ecosystem

Unlike legacy stacks - OBIA, ODI, siloed data centres - FDI is built on Oracle’s next-generation Data Intelligence Platform. It blends data lakes, Autonomous Data Warehouse, Oracle Analytics Cloud, OCI AI services, and GoldenGate streaming into a seamless, managed ecosystem  . This means organisations can now handle batch and real-time data, include external sources and apply AI/ML—all within one secure environment. 

This is Oracle's vision as Data Intelligence Platform has been announced but is not yet generally available. 

🔄 Consistent Insights Across Pillars

FDI’s architecture supports conformed dimensions and shared semantic models spanning finance, HR, SCM, and CX. This allows for unified KPIs and analytics, enabling stakeholders to ask and answer cross-domain questions like:

• “How is workforce turnover impacting revenue?”
• “What supply chain inefficiencies are driving higher costs?”

The result is enterprise-wide analytics based on a single source of truth  .

💡 Full Extensibility with Governed Access

As part of Oracle’s Data Intelligence Platform, FDI offers extensive extensibility. Users can bring in external datasets, extend semantic models, build custom analytics, and consume OCI AI services - all within Oracle’s security framework. Governed self-service means broad analytical freedom without compromising data integrity  .

🛠 Evergreen Platform, Zero Infrastructure Burden

The platform is fully managed and evergreen. Oracle handles everything - from provisioning, patching, tuning, and upgrades to integrating the latest AI services. Teams can focus on driving value rather than
wrestling with infrastructure  .

As you’ve seen, Fusion Data Intelligence delivers a fully managed, cloud-native analytics ecosystem - bringing together Fusion SaaS, Oracle’s Autonomous Data Warehouse, and Analytics Cloud under one secure, AI-enhanced platform. It unifies data across domains, embeds intelligent insights and governance, and eliminates legacy complexity - truly delivering on Oracle’s vision of a Data Intelligence Platform. Now it’s your turn: take a moment to reflect on how FDI could accelerate insight‑driven transformation in your organisation. 

Over the years, many of us working in the Oracle analytics space have helped customers implement Oracle Business Intelligence Applications (OBIA) - a powerful solution in its time, offering prebuilt analytics across ERP, HCM and more. If you ever spent hours managing DAC, tweaking ETL mappings, or retrofitting OBIA customisations after a patch - you’ll understand why Fusion Data Intelligence feels like Oracle finally got analytics right.But let’s be honest: it had its fair share of complexity, rigidity, and technical debt.
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Fast-forward to today and we’ve entered a new era with Oracle Fusion Data Intelligence (FDI) - a reimagined, cloud-native analytics platform designed from the ground up for the Fusion SaaS landscape. And if you’ve ever battled with OBIA’s extensibility, upgrade cycles or data latency, FDI is likely to feel like a breath of fresh air.

This post is the first in a short series unpacking what FDI actually is, how it compares with its predecessors, and what it means for Fusion customers today.

Oracle's recent growth

Over the past 2–3 years, Oracle has consistently grown its cloud business, with total revenue rising from $40.5 billion in FY2022 to $57.4 billion in FY2025, driven largely by strong momentum in Fusion Cloud Applications, NetSuite, and OCI (Oracle Cloud Infrastructure).

While Oracle doesn’t match the scale of hyperscalers like AWS or Microsoft Azure in infrastructure alone, its distinct advantage lies in its full-stack strategy - uniquely offering enterprise SaaS, infrastructure, and the database layer under one roof. This vertically integrated model means Oracle can optimise performance, security, and cost across its stack, especially for Fusion workloads. Competitors like SAP and Workday lead in applications but lack native cloud infrastructure; AWS and Azure dominate infrastructure but rely on third-party SaaS partners.

​Oracle, by contrast, continues to blur the lines between application and platform, using technologies like Autonomous Database, OCI Gen2, and now Fusion Data Intelligence to deliver insights that are deeply embedded, secure, and performant - all within its own ecosystem.

These figures aren’t just impressive - they’re a strong signal that Oracle’s SaaS portfolio is achieving scale and maturity, particularly in core enterprise functions like Finance, HR, and Operations. Fusion ERP alone has grown from $0.9B to $1.0B in quarterly revenue, underscoring widespread enterprise adoption.

From Adoption to Insight: The Next Frontier

​As organisations continue investing in Oracle Fusion Cloud applications, the expectation isn’t just automation - it’s intelligence. Businesses aren’t content with simply moving transactional processes to the cloud; they want to understand the return on those investments, monitor performance in real time, and use their data to make faster, smarter decisions.
This is where Fusion Data Intelligence (FDI) steps in.
Just as Oracle’s adoption of Fusion SaaS pillars is accelerating, so too is the demand for embedded, governed, cross-functional insights that empower users in the flow of work. With SaaS platforms becoming the new systems of record, the analytics layer must evolve in lockstep - and be natively integrated, secure, and scalable.
FDI is that evolution.

Why FDI Matters Now More Than Ever

• Data gravity has shifted - core operational data now lives in Fusion Cloud ERP, HCM, SCM, and CX.
• Decision-makers want answers in context - not in a separate BI tool, but embedded inside the applications they use every day.
• Cloud-native analytics isn’t a nice-to-have; it’s a business requirement for agility, accountability, and optimisation.

​FDI bridges this critical gap by turning raw operational data into actionable intelligence - all while aligning with the Fusion application security model, lifecycle, and extensibility standards.

But OBIA came with constraints that, over time, became significant limitations:

• Customisations were fragile: Even minor changes to the ETL or data model could break during upgrades, making custom development expensive and hard to maintain.
• Siloed architectures: Each functional pillar (e.g. Oracle EBS, PeopleSoft, Siebel, JDE) had its own data model and ETL codebase, with no unified customer or product view.
• Upgrade pain: OBIA upgrades were major projects in themselves - often requiring reimplementation or heavy retrofitting for customised solutions.
• Customer-managed infrastructure: Customers had to provision, maintain, and tune on-premises environments — including DAC, Informatica, BI Server, and database platforms - with all the associated complexity and cost.
• Slow to evolve: The on-prem model struggled to keep up with rapidly changing business requirements and the rise of cloud-based enterprise applications.

The Modern Alternative: Fusion Data Intelligence

With Fusion Data Intelligence (FDI), Oracle has reimagined what enterprise application analytics should look like in the cloud era.

• Extensibility is core, not an afterthought: FDI is metadata-driven and designed to be extended - securely, scalable, and without breaking with every update.
• Unified cross-pillar model: Instead of siloed data marts, FDI provides a 360-degree customer, employee, and transaction view across Fusion ERP, HCM, SCM, and CX — built on a shared semantic model.
• Evergreen analytics: As Fusion Apps evolve, so too does FDI — delivered as a SaaS analytics layer that evolves in sync with Oracle’s application roadmap.
• Oracle-managed infrastructure: FDI is provisioned, patched, secured, and optimised by Oracle - no DAC, no Informatica, no infrastructure headaches.
• AI and machine learning embedded: Insights aren’t just historical - FDI includes predictive models, anomaly detection, and natural language queries right out of the box

From OBIA to OAX to FAW to FDI: An Analytics Evolution

FDI didn’t appear out of nowhere - it’s the result of five years of iterative development across multiple product identities. It began as Oracle Analytics for Applications (OAX), introduced around 2019 as a cloud-based successor to OBIA. OAX was designed to deliver prebuilt analytics for Oracle Fusion Cloud Applications, leveraging Oracle Autonomous Data Warehouse and Oracle Analytics Cloud. In 2020, OAX was rebranded as Fusion Analytics Warehouse (FAW), marking a shift toward a more unified, extensible platform. FAW introduced modular “pillars” aligned with business domains--ERP, HCM, SCM, and CX—each offering curated data models, semantic layers, and prebuilt KPIs. Over the next few years, Oracle expanded these pillars with hundreds of subject areas and embedded machine learning for predictive insights.

In 2024, FAW was renamed Fusion Data Intelligence (FDI). This rebranding emphasized its broader mission: not just warehousing analytics, but enabling intelligent decision-making across the enterprise. FDI retained the core architecture—Autonomous Data Warehouse, Oracle Analytics Cloud, and managed pipelines—but added enhanced extensibility, data sharing capabilities, and a more intuitive console for governance and customisation.

Looking Ahead

​This post was just the beginning. Over the next few instalments, we’ll dive deeper into the nuts and bolts of Fusion Data Intelligence - from how it handles extensibility and embedded insights, to what it means for Fusion customers trying to move beyond dashboards and into decision intelligence.

FDI represents more than just a new analytics tool - it’s a shift in how Oracle customers can extract value from their SaaS investments. If you’ve ever found yourself battling data silos, struggling with upgrades, or explaining to stakeholders why reporting still takes days, this series is for you. Stay tuned.