Idea / Enhancement Request
Oracle Analytics Dataflows already allow users to use datasets and subject areas as inputs, and Dataflow outputs can be saved to supported database targets. However, in FDI the missing capability is a first-class governed writeback workspace model for business users and power users.
FDI should provide an option such as “Save to FDI Workspace Table” within Dataflows. This would allow authorized users to persist curated Dataflow outputs into governed personal, team, project, or business-area schemas in the FDI Autonomous AI Lakehouse without needing broad ADW administrator access or manual DBA-driven schema setup.
Business Problem
Business users often need to combine FDI subject-area data with external, local, departmental, planning, R&D, innovation, or project execution data. Today, they can create datasets and Dataflows, but persisting those outputs into a governed ADW schema requires additional technical setup, custom schemas, grants, connection management, and administrative oversight.
This creates friction for self-service analytics. Users either keep outputs as isolated datasets, rely on spreadsheets, or ask IT to create and manage custom warehouse structures. This limits agility and makes it harder to build reusable, performant, governed data products inside FDI.
Requested Enhancement
Please introduce governed Dataflow writeback workspaces in FDI with:
- Personal, team, project, and business-area writeback schemas.
- Native “Save to FDI Workspace Table” option in Dataflows.
- Admin-managed storage quotas and compute guardrails.
- Ability to create, replace, append, and merge Dataflow outputs.
- Security controls so users can write only to approved schemas.
- Ability to inherit or reapply FDI data security on shared outputs.
- Lineage showing subject areas, datasets, files, and Dataflows used to create each output.
- Promotion workflow from personal output to team-certified or enterprise-certified data product.
- Lifecycle controls for retention, archival, cleanup, and deprecation.
- Monitoring for refresh status, failures, usage, storage, and downstream dependencies.
Use Case
A finance, HR, SCM, CX, project, R&D, or analytics power user needs to combine FDI-secured subject-area data with a local file or departmental dataset, create a curated output, and reuse it across multiple workbooks. The user should be able to write the result into a governed FDI workspace table, refresh it on a schedule, and share it with the appropriate team without requiring broad ADW access.
Business Value
This would allow business-led data product creation while preserving enterprise governance. It would reduce spreadsheet proliferation, improve performance, avoid unnecessary data duplication, and give IT better control over security, storage, lineage, and lifecycle management.
Expected Outcome
FDI should support governed self-service writeback into Autonomous AI Lakehouse as a native product capability, not only through manual custom schemas and administrator-managed database grants.
