Oracle Cloud ERP and the broader Oracle application stack generate an extraordinary amount of operational and financial data—but most organizations struggle to convert that data into trusted, analytics-ready outputs at the pace the business expects. The typical symptoms are familiar to OATUG attendees: brittle nightly jobs, inconsistent definitions across teams, long lead times for new extracts, and “shadow pipelines” living in spreadsheets or one-off scripts that no one wants to own.
This webinar reframes the challenge as a data delivery problem—then shows how a modern data pipeline approach can create an “analytics supply chain” from Oracle source systems to curated datasets used in reporting, planning, and AI initiatives. We’ll use Data Pipelines to anchor a practical discussion on orchestration, automation, monitoring, incremental loads, data quality checks, and governance patterns that improve reliability while reducing dependency on scarce engineering bandwidth.
Whether you’re building a finance data mart, enabling self-service BI, or preparing Fusion data for downstream platforms, this session will help you design pipelines that are scalable, observable, and built for change.
Learning Objectives:
- Map common Oracle analytics failure points to pipeline design and operating-model fixes
- Learn how to structure extraction, transformation, validation, and publishing for repeatable delivery
- Understand monitoring and auditability concepts that improve trust and reduce firefighting
- See practical patterns for blending Oracle Cloud data with other enterprise sources-without chaos
Presenters: