Oracle Fusion 26B Introduces a New Data Extraction Framework: Goodbye BICC, Hello Read-Only Data Store

                                    Oracle Fusion 26B Data Extraction | BICC Replacement Guide

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

All of these workloads compete for the same database resources. As data volumes grow, this can impact application performance and increase extraction times.

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.

Oracle Fusion 26B, Oracle Data Extraction, Oracle BICC Replacement, Oracle Autonomous Data Warehouse, Oracle Redwood, Oracle Fusion Reporting, Oracle Fusion Analytics, Oracle Business Objects, Oracle Cloud ERP 26B, Oracle Data Integration

Oracle fusion AI Agent Pricing Explained (2026): When Is It Free, When Does It Become Chargeable?

Oracle Fusion AI Agent Pricing Explained 2026 | Free vs Chargeable AI Agents

Learn when Oracle Fusion AI Agents are free, when they become chargeable, how AI Units work, and how Oracle calculates AI costs in Oracle Fusion Cloud.

Oracle AI Agent Pricing

Oracle Fusion AI Agent Pricing Explained: Free vs Pricing

Oracle Fusion is making AI a core part of Oracle Fusion Cloud Applications. Whether you're using ERP, HCM, SCM, CX, or Procurement, AI Agents can automate repetitive work, answer business questions, and improve productivity.

One of the most common questions customers ask is:

"Is Oracle fusion AI Agent Studio free, or do I have to pay for every AI Agent I build?"

The answer depends on what you're building and which AI model you're using.

Let's break it down.

What's Included with Oracle Fusion?

If you're an Oracle Fusion Cloud customer, several AI capabilities are already included with your subscription.

You can typically access:

• Oracle AI Agent Studio

• Oracle-delivered AI Agents

• AI Agent Marketplace

• Built-in monitoring and analytics

• Monthly AI Unit allocation (subject to your subscription)

This allows organizations to explore AI without making an immediate investment in additional AI services.

When Does Oracle Start Charging?

Oracle's latest AI pricing model is based on AI Units, not simply on the number of AI Agents you create.

In general, AI consumption starts becoming relevant when:

• Premium AI models are used

• AI Unit consumption exceeds the allocation included with your subscription

• Agentic Applications are deployed to production (where applicable)

• Additional AI Units need to be purchased

The key takeaway is that the AI model and workload drive costs more than the number of agents.

What Are AI Units?

Think of AI Units (AUs) as Oracle's way of measuring AI usage.

Every AI interaction consumes resources, such as:

• Running an AI model

• Processing documents

• Calling enterprise APIs

• Generating responses

Instead of charging separately for each action, Oracle measures overall AI consumption using AI Units.

User Request
      │
      ▼
Oracle AI Agent
      │
      ▼
LLM Processes Request
      │
      ▼
AI Units Consumed

When Does an Oracle Fusion AI Agent Become Chargeable?

This is the question almost every Oracle Fusion customer asks.

The simple answer is:

Your AI Agent doesn't become chargeable just because it's custom. It becomes chargeable when it starts consuming billable AI Units—primarily through the use of Premium LLMs or when your included AI Unit allocation is exceeded.

Scenario 1: Using Oracle's Basic LLM (No AI Unit Charges)

If your AI Agent uses Oracle's Basic LLM (for example, GPT-OSS), Oracle does not deduct AI Units for standard AI interactions. Whether you're using an Oracle-delivered agent, a modified agent, or even your own custom-built agent, the AI model itself does not generate AI Unit charges in this scenario.

Examples:

• HR Policy Assistant

• Leave Balance Agent

• Procurement Help Agent

• A custom agent built with GPT-OSS

These remain within the included capabilities as long as you stay on the supported Basic LLM and don't consume chargeable premium AI services.

Scenario 2: Using a Premium LLM (AI Units Start Consuming)

The moment you switch your AI Agent to a Premium LLM, Oracle starts measuring AI usage through AI Units (AUs).

Examples of Premium LLMs include:

• GPT-5 mini

• GPT-4.1 mini

Each AI interaction consumes AI Units based on:

• The selected LLM

• Prompt size

• Response size

• Document processing

• Workflow complexity

In Oracle's published examples, a typical premium AI interaction may consume around 5 AI Units, although actual consumption varies by workload.

How Many AI Units Do You Get for Free?

Every eligible Oracle Fusion subscription includes a monthly allocation of 20,000 AI Units.

Think of it as a monthly AI allowance.

Oracle Fusion Subscription
          │
          ▼
 20,000 AI Units / Month
          │
          ▼
Used by Premium AI Requests
          │
          ▼
When the allocation is exhausted,
additional AI Units must be purchased.

Unused AI Units do not roll over to the next month—they reset with each billing cycle.

How Are AI Units Consumed?

AI Unit consumption depends on the type of work your agent performs.

The key takeaway is that AI Units are consumed based on AI processing, not simply because an agent exists.

So, Is It the Agent or the LLM That Determines Cost?

The easiest way to think about Oracle's pricing model is:

• Standard Agent + Basic LLM = Included with your subscription (subject to Oracle's licensing terms).

• Custom Agent + Basic LLM = AI Unit charges generally don't apply for the Basic LLM itself, though other licensing considerations may still apply.

• Any Agent (Standard or Custom) + Premium LLM = AI Units are consumed.

• Once your included monthly AI Unit allocation is exhausted, you'll need to purchase additional AI Units to continue using premium AI capabilities.

Key Takeaway

The biggest misconception is that "custom agents cost money."

Under Oracle's current AI Units model, the primary driver of cost is the AI model (LLM) and the amount of AI processing performed—not whether the agent is Oracle-delivered, modified, or custom. Choosing a Premium LLM and increasing AI usage will consume your monthly AI Unit allocation. Once those included AI Units are exhausted, additional usage becomes chargeable.

Disclaimer: Oracle updates AI capabilities, licensing policies, and pricing with each release. Always refer to the latest Oracle Fusion Cloud documentation, Oracle AI pricing guides, and Oracle Cloud Service Price List before making licensing or purchasing decisions. How oracle charges for ai agents ?

 Oracle Fusion Data Extraction Tool Explained | Features, Benefits & Use Cases

Introducing Oracle Fusion’s New Data Extraction Tool: A Game-Changer for Reporting

Discover Oracle Fusion’s new data extraction tool designed for faster reporting and seamless BI integration. Learn key features, benefits, and real-world use cases to optimize your data strategy.

Introduction to Oracle Fusion Data Extraction Tool

In today’s data-driven landscape, organizations using Oracle Fusion applications need faster, more flexible ways to access and analyze their data. To address this need, Oracle has introduced a powerful new data extraction tool within Oracle Fusion—designed to simplify reporting, improve performance, and enhance user control.

This article breaks down everything you need to know about this latest feature and how it can transform your reporting workflows.

What is Oracle Fusion’s Data Extraction Tool?

Oracle Fusion’s new data extraction tool is an advanced capability that enables users to efficiently pull large volumes of data directly from Fusion applications. It is specifically built to support reporting, analytics, and integrations without placing heavy loads on transactional systems.

Unlike traditional reporting methods, this tool provides a streamlined and scalable approach to data extraction, making it ideal for business intelligence (BI) and external reporting needs.

How to Enable and Use Oracle Fusion Data Extraction Tool (Step-by-Step)

Step 1: Enable the Data Extraction Tool in Oracle Fusion

To get started, the feature must be enabled from the setup configuration:

• Navigate to Setup and Maintenance
• Search for the relevant offering (currently under Manufacturing / Supply Chain)
• Locate the feature: - “Redwood: Extract Application Data from a Read-Optimized Data Store”
• Enable (opt-in) the feature

Once enabled, the tool will become available in the Tools menu.

Note: You may also need to raise a Service Request (SR) with Oracle Support to fully activate the functionality.

Step 2: Configure Required Profile Option

Next, you must enable a specific profile option to allow integration:

• Go to: Setup and Maintenance
• Open: Manage Administrator Profile Values

• Search for profile code:
• ORA_ASE_SAS_INTEGRATION_ENABLED

          Set the value at Site level = Yes

• Save the changes

This step ensures the backend integration required for data extraction is active.

Step 3: Create and Assign Security Role

Security configuration is critical for accessing the tool.

• Create a Custom Role:
• Navigate to Tools → Security Console
• Click Create Role
• Provide a role name (e.g., Data Extraction Role)
• Select appropriate role category
• Enable Permission Groups

Add Required Roles:

Include the following roles in the hierarchy:

• ESS Admin
• OBIA Extract Transform Load (RWD)
• Supply Chain Integration Specialist

Assign Role to User:

• Go to Users section
• Assign the newly created role to your user account
• Save changes

This ensures proper access control and permissions.

Step 4: Access the Data Extraction Tool

Once setup is complete:

• Navigate to Navigator → Tools → Data Extraction
• Open the application

You will see three main sections:

• Extract Definitions : Configure what data to extract and how
• Extract Schedules : Set one-time or recurring extraction jobs
• Extract Jobs : Monitor past and ongoing extraction runs

These sections control the entire extraction lifecycle.

Step 5: Create a New Extract Definition

To extract data:

• Click “+” (Create Extract)
• Enter:
• Name
• Description (optional)
• Extract date (if required)

                                      

Select Output Format:

• CSV (default)
• JSON

Choose Data:

• Select business area (e.g., Supply Chain, Finance)
• Drill down to functional module (e.g., Order Management)
• Choose objects (e.g., Sales Orders)
• Select required attributes/fields

This step defines what data will be extracted.

Step 6: Schedule or Run Extract

You can now execute the extract:

• Run on-demand (manual)
• Or create a scheduled job for automation

Scheduling ensures continuous data availability for reporting and analytics.

Step 7: Monitor Extract Jobs

Finally, track your extraction:

• Go to Extract Jobs
• Check:
• Status (Running / Completed / Failed)
• Execution logs
• Errors (if any)
• Once completed, data files are securely uploaded to UCM (Universal Content Management).
• Retrieve your extract:
• Visit your UCM instance (usually hostname/cs).
• Navigate to Content Management > Checked Out Content.
• Search with the Request ID from your extraction job.
• Download the generated zip file containing your data and metadata in CSV format.

This helps in troubleshooting and managing data pipelines effectively.

Key Features of the New Data Extraction Tool

1. High-Performance Data Extraction

The tool is optimized for extracting large datasets quickly and efficiently. It minimizes system impact, ensuring that your Oracle Fusion environment continues to perform smoothly.

2. Flexible Data Selection

Users can define exactly what data they need by applying filters, selecting attributes, and customizing extraction criteria. This flexibility helps reduce unnecessary data processing.

3. Seamless Integration with BI Tools

The extracted data can be easily integrated with popular BI and analytics tools, allowing organizations to generate insights without complex transformations.

4. Scheduled and Automated Extracts

Automation is a key advantage. You can schedule data extraction jobs to run at specific intervals, ensuring that your reports are always up to date.

5. Improved Data Accuracy and Consistency

By extracting data directly from Oracle Fusion in a structured format, the tool ensures high data accuracy, reducing discrepancies in reporting.

Benefits of Using Oracle Fusion Data Extraction Tool

Faster Reporting

With quicker data extraction, reporting cycles are significantly reduced. Teams can access insights faster and make timely decisions.

Reduced System Load

Traditional reporting methods often slow down transactional systems. This tool minimizes that impact, improving overall system performance.

Enhanced Data Accessibility

Business users can access the data they need without relying heavily on IT teams, promoting self-service analytics.

Better Decision-Making

Accurate and timely data leads to more informed decisions, giving organizations a competitive edge.

Oracle Fusion’s new data extraction tool is a major step forward in simplifying enterprise reporting and analytics. With its high performance, flexibility, and integration capabilities, it empowers organizations to unlock the full value of their data.

If you’re using Oracle Fusion applications, adopting this tool can significantly improve your reporting efficiency and data strategy.