Business teams can validate outcomes earlier and refine requirements with real data in Databricks.
Orbit Analytics transforms Oracle Fusion data into real-time insights with AI-powered BI and no-code data pipelines. The Orbit DataJump integration with Databricks automates data movement to the Lakehouse, enabling analytics-ready models and AI-powered decision-making for finance, supply chain, and HR.
In Orbit DataJump, you select Oracle Fusion as your source connector. DataJump supports Fusion extraction mechanisms, including BICC, BI Publisher (BIP), Custom SQLs, and EPM or EDM REST APIs. DataJump also handles schema discovery and authentication during setup.
Next, you set Databricks as the destination by providing the workspace details and selecting the target database and storage. Orbit DataJump creates the schema and prepares optimized write paths for bulk and incremental loads.
You choose what to extract (for example, BICC PVOs and columns, or an existing BI Publisher report). Then you run an initial load and schedule incremental loads. Monitor runs from the Orbit console, with DataJump handling data validation, error retries, and schema drift to maintain pipeline stability.
Orbit DataJump provides the ingestion foundation and operational reliability, while Databricks provides the unified platform for analytics and AI. Together, this creates a practical path from Oracle ERP transactions to governed analytics outcomes. Learn more
Designed for Oracle Fusion extraction realities so ERP data lands cleanly and consistently, even as reporting requirements evolve.
Get the practical integration guide for moving Oracle Fusion ERP data into Databricks with stable, repeatable pipelines using Orbit DataJump.
Support growing data volumes and expanding analytics demand without constantly reworking pipelines or creating parallel processes.
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Produce trusted datasets that teams can reuse across dashboards, semantic layers, and AI initiatives without redefining metrics every time.
Teams typically start this journey to reduce manual reporting work, build a single source of truth, and enable advanced analytics. The key requirement is repeatability, because what works for a pilot must also work during quarter close, audit requests, and ongoing operational reporting.
Business teams can validate outcomes earlier and refine requirements with real data in Databricks.
Requires less maintenance than custom-built pipelines, which break when source structures or reporting needs change.
Get monitoring and clear run visibility, which helps analytics teams and business stakeholders stay aligned.
Enable BI, advanced analytics, and AI initiatives so teams can focus on insights instead of extraction and rework.
"The tool helps us seamlessly build pipelines to extract data from Oracle Fusion into Databricks. It is truly impressive, very user-friendly, significantly reduces development effort, and provides a wide range of source and destination adapters". - Madhu Chava, Cloud Solutions Engineer, MARTA
Designed for Oracle Fusion extraction realities so ERP data lands cleanly and consistently, even as reporting requirements evolve.
Read Now >Get the practical integration guide for moving Oracle Fusion ERP data into Databricks with stable, repeatable pipelines using Orbit DataJump.
Read Now >Support growing data volumes and expanding analytics demand without constantly reworking pipelines or creating parallel processes.
Read Now >Produce trusted datasets that teams can reuse across dashboards, semantic layers, and AI initiatives without redefining metrics every time.
Read Now >