Oracle Fusion 26B Introduces a New Data Extraction Framework: Goodbye BICC, Hello Read-Only Data Store
Oracle Fusion 26B Introduces a Smarter Way to Extract Data – Here's Why It Matters
If your organisation relies on Power BI, Oracle Analytics Cloud (OAC), Snowflake, Microsoft Fabric, or any external reporting platform connected to Oracle Fusion Cloud, Oracle 26B brings one of the most significant platform enhancements in recent years.
Oracle has introduced a new Data Extraction Framework that fundamentally changes how application data is extracted from Oracle Fusion.
The Challenge with Traditional Data Extraction
For years, Oracle Fusion customers have used tools like:
- BI Cloud Connector (BICC)
- BI Publisher
- OTBI
- Custom SQL-based integrations
to extract business data for reporting, analytics, and downstream applications.
The problem?
All these extraction jobs accessed the same production database that users relied on for day-to-day business operations.
Imagine your finance team is posting journals during month-end close while, at the same time:
- Power BI is refreshing dashboards
- A data warehouse is extracting millions of records
- Integration jobs are pulling supplier and invoice data
- Business analysts are running large reports
How Oracle Fusion 26B Changes Everything
Oracle's new Data Extraction Framework solves this challenge by introducing a Read-Only Replicated Data Store powered by Oracle Autonomous Data Warehouse (ADW).
Instead of extracting data directly from the transactional Oracle Fusion database, Oracle continuously replicates business data into a dedicated read-only environment.
Your reporting and integration tools now connect to this replicated data store rather than the live production system.
Production users and reporting workloads are now separated, resulting in a more scalable architecture.
Why This Is a Big Deal
This isn't simply a new user interface or another Redwood enhancement.
It changes the architecture of Oracle Fusion reporting.
Instead of running analytical workloads on your production environment, Oracle now follows the same best practice used by modern cloud platforms:
Operational Workloads → Production Database
Reporting & Analytics → Read-Only Analytics Database
This separation significantly improves system performance and data availability.
New Features Introduced in Oracle 26B
Oracle Is Replacing BICC
Perhaps the biggest announcement is Oracle's recommendation that customers adopt this framework for all new extraction use cases.
Over time, this framework is expected to replace:
- BI Cloud Connector (BICC)
- BI Publisher-based extraction
For organizations planning new reporting or integration projects, this is the strategic direction Oracle is investing in.
Real Business Example
Imagine a global retail company with operations in 20 countries.
Every hour, it refreshes dashboards showing:
- Sales performance
- Supplier payments
- Inventory
- Purchase orders
- Financial KPIs
Before Oracle 26B
These refreshes query the production Oracle Fusion environment, competing with finance users processing invoices and journals.
After Oracle 26B
The dashboards connect to the replicated Autonomous Data Warehouse.
Finance users continue working without reporting workloads affecting application performance.
The result is faster reporting and a smoother user experience.
Final Thoughts
Oracle Fusion 26B's new Data Extraction Framework is much more than a replacement for BICC—it's a foundational change in how Oracle envisions enterprise reporting and data integration.
By moving extraction workloads to a dedicated, read-only Autonomous Data Warehouse, Oracle delivers a modern architecture that improves performance, simplifies development, and prepares organizations for the next generation of analytics and AI.
For customers starting new reporting, data warehouse, or integration initiatives, adopting this framework from the outset will help align with Oracle's long-term roadmap while reducing complexity and improving scalability.
As Oracle continues investing in Redwood, AI, and cloud-native services, this new Data Extraction Framework is likely to become the standard approach for accessing Oracle Fusion data.
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