Introduction: Why Databricks for Oracle Fusion ERP Data?

Enterprises running Oracle Cloud ERP are generating massive volumes of financial and operational data every day. But running static reports within Oracle Fusion is not enough. To gain a competitive edge, companies want to:

• Train machine learning models on ERP + external datasets
• Predict financial and operational outcomes (e.g., cash flow, demand, anomalies)
• Blend ERP data with IoT, CRM, and supply chain signals
• Move toward AI-powered decision-making

This is why more Oracle Fusion customers are turning to platforms like Databricks. With its Delta Lake architecture, Databricks provides the scalability, flexibility, and performance needed for advanced analytics and ML workloads.

In this post, we highlight the role of a modern data pipeline solution like Orbit’s Data Pipeline that’ll make life easier for both technology and operational leaders to “move” data from Oracle Cloud ERP to a platform like Databricks – where AI/ML and advanced analytics workloads can be run.

The Integration Challenge

Connecting Oracle Fusion ERP to Databricks is not straightforward:

• Manual extracts (BICC/OTBI) are fragile and error-prone

• Custom ETL pipelines require deep technical expertise

• Latency issues slow down real-time analytics use cases

• Governance and security become harder to enforce without automation

This results in IT and data engineering teams spending time building and maintaining pipelines, while finance and operations leaders keep waiting for insights!

Orbit’s Role: Simplifying data jump from Fusion ERP to Databricks with Modern Data Pipeline Solution from Orbit

Orbit solves this with Orbit DataJump, a no-code data pipeline engine built for Oracle Fusion ERP.

• Automated Ingestion: Move Fusion ERP data into Databricks Delta Lake with minimal setup.

• Low-Code/No-Code Configurations: Finance or analytics leaders don’t need to write ETL scripts.

• Real-Time Updates: Keep ERP data synced for ML workloads without refresh delays.

• Built-in Governance: Data validation, monitoring, and scheduling ensure accuracy.

With Orbit, enterprises can focus on using Databricks for analytics instead of wasting time on integration.

Use Cases: What You Can Achieve with Fusion ERP + Databricks with the help of Orbit

• Predictive Cash Flow Forecasting: Train ML models on AP/AR and GL data to anticipate cash positions and liquidity risks.

• Supply Chain Demand Prediction: Blend ERP procurement data with supplier performance and IoT data to forecast disruptions.

• Expense Anomaly Detection: Identify irregular spend patterns by applying ML algorithms to ERP expense data.

• Financial Variance Analysis: Use real-time ERP + external data to run “what-if” scenarios with predictive accuracy.

Orbit Data Pipeline vs. Manual Pipelines: A Step-by-Step Comparison

Step	Manual Approach	Orbit Data Jump
Data Extraction	Custom OTBI/BICC scripts	Pre-built Fusion ERP connectors
Data Load	Custom ETL jobs to Delta Lake	No-code, automated pipelines
Refresh Frequency	Batch, delayed	Near real-time sync
Governance	Manual monitoring	Built-in validation & scheduling
Outcome	Delays, errors, IT dependency	Fast, accurate, ML-ready datasets

Conclusion: AI-Ready ERP Analytics with Orbit + Databricks

Oracle Fusion ERP holds the keys to your most critical financial and operational insights. But only by integrating it with Databricks can you unlock predictive and AI-driven outcomes.

Orbit makes this seamless. With Orbit Data Pipeline Solution, you can:

• Ingest Fusion ERP data directly into Delta Lake

• Eliminate manual ETL complexity

• Power your machine learning and advanced analytics workloads

With Orbit, you can make ERP data, ML-ready — in hours, not months.

FAQs: Oracle Fusion ERP + Databricks

1. Why integrate Oracle Fusion ERP with Databricks?

To enable advanced analytics, AI/ML workloads, and predictive modeling on ERP financial and operational data.

2. Can I connect Fusion ERP to Databricks without Orbit?

Yes, but it usually requires manual extracts and custom ETL, which are slower, harder to maintain, and less reliable.

3. How does Orbit improve Fusion ERP → Databricks pipelines?

Orbit automates ingestion into Delta Lake with low-code/no-code pipelines, built-in governance, and real-time sync.

4. What ML use cases work best with Fusion ERP + Databricks?

Cash flow forecasting, demand prediction, anomaly detection, and predictive financial analytics.

5. Is this suitable for multi-cloud environments?

Yes. Orbit pipelines work across cloud ecosystems, so your ERP can connect to Databricks regardless of infrastructure.