Oracle Fusion Data Delivered
to Snowflake.
In Hours, Not Months.
Automate Oracle Fusion pipelines to Snowflake with plug-and-play
pipeline templates. No missing file extracts. No manual exports.
No ETL projects.
The real problem
Building the Pipeline Is Easy. Extracting Fusion Data Isn't.
Before the Oracle Fusion data reaches Snowflake, most teams end up building one of these approaches first.
BICC Extracts
Manage file-based exports, decode Public View Objects (PVO), and combine multiple files before loading data into Snowflake.
Custom Oracle Extraction
Build Oracle authentication, pagination, watermark tracking, retries, and incremental loading logic for each pipeline.
DIY Pipelines
Design, configure, test, and deploy your Oracle Fusion pipeline from scratch instead of starting with a ready-to-deploy template.
Pipeline Maintenance
Maintain custom extraction code, handle schema changes, and troubleshoot pipeline failures.
Choose BI Connector.
Instead of building the Oracle Fusion extraction layer..
Reuse one that's already built.
Start Free Trial
How it works
How BI Connector Loads Oracle Fusion Data into Snowflake
01
Connect
Connect securely to Oracle Fusion base tables,
BI Publisher data models, Fusion SQL queries,
OTBI analyses, and BICC PVOs.
BI Publisher data models, Fusion SQL queries,
OTBI analyses, and BICC PVOs.
02
Configure
Generate the lookup table in BI Connector,
import the pre-built pipeline template, and map
the source and destination connections.
import the pre-built pipeline template, and map
the source and destination connections.
03
Deliver
ADF or Fabric orchestrates pipeline execution,
while BI Connector manages extraction,
chunking, retries, refreshes, and delivery.
while BI Connector manages extraction,
chunking, retries, refreshes, and delivery.
Architecture
Seamless Oracle Fusion Data Delivery to Your Azure Stack.
Benefits
What Changes for Your Team
Eliminate Oracle Extraction Complexity
Replace BICC file exports, custom APIs, and
file-based workflows with Oracle-aware extraction
built for Fusion.
Keep Azure Data Factory or Fabric
Keep Azure Data Factory or Fabric as your orchestration platform while BI Connector handles extraction and refresh logic.
Incremental Data Refresh
Support initial full loads followed by automated incremental refreshes that process only new and changed Fusion data.
Build on Your Snowflake Data
Load Fusion data into Snowflake to build tables, views, transformations, and enterprise data models using your existing workflows.
Reduce Pipeline Maintenance
Offload Fusion extraction and maintenance to BI Connector so you can focus on Snowflake analytics and data products.
Accelerate Implementation
Start moving Oracle Fusion data into Snowflake in hours instead of spending weeks building Oracle-specific extraction logic.
Customer stories
Trusted by Enterprise Data Engineering Teams
Organizations use BI Connector to simplify Oracle Fusion extraction while continuing to use Azure Data Factory or Fabric and Snowflake
as part of their existing data platform.
“What took months
now takes hours.”
“We cut
Oracle reporting costs
by over 80%.”
“A game-changer for
Oracle Fusion data
warehouse integration
at scale.”
Comparison
Why Teams Use BI Connector for Oracle Fusion to
Snowflake Data Pipeline
Build it yourself
With BI Connector
Build custom Oracle Fusion extraction logic
Manage BICC files and PVOs
Develop full and incremental refresh logic
Build retry, chunking, and UPSERT logic
Build custom ADF pipeline components
Spend weeks integrating Oracle Fusion