In today’s data-driven enterprises, real-time insights across diverse systems are crucial. Yet integrating Oracle Cloud Applications with Google BigQuery at scale means dealing with inconsistent schemas, brittle pipelines, and long development cycles. Incorta Connect was built to address these exact challenges—offering a high-performance, schema-aware, and fully observable data delivery platform.
This blog highlights how Incorta Connect streamlines end-to-end data integration from Oracle Cloud Applications to Google BigQuery and why it outperforms traditional ELT frameworks for this use case.
1. Connect: Native Oracle Integration
Incorta offers native connectors for Oracle Cloud Applications, supporting both:
- Oracle Business Intelligence Cloud Connector (BICC) – the gold standard for bulk data exports using Public View Objects (PVOs).
- Business Intelligence Publisher (BIP) – for custom data extraction, where standard PVOs are not available
While BICC is ideal for extracting standard data sets, it has limitations when certain PVOs don’t capture all relevant fields. To address these gaps, Incorta Connect’s BIP-based integration lets users run custom SQL queries directly on Oracle source tables. This eliminates the need to manually create and manage BIP reports and empowers teams with ad hoc data access.
2. Extract, Load & Transform: Semantic Data Modeling
Incorta Connect not only extracts and loads data but also understands data relationships, hierarchies, and metadata from Oracle Cloud Applications. It enables seamless data unification by connecting Oracle data with other enterprise sources in a centralized semantic layer.
Unlike legacy ETL pipelines that require modeling data in the rigid physical schemas, Incorta Connect allows users to define business-friendly metrics and dimensions in a low / no code interface in the semantic layer. Think hundreds of reusable star schemas configured as logical views over raw or joined data, which can then be pushed to BigQuery or any Data Warehouse or Lakehouse of your choice.
This gives users the flexibility to iterate on business definitions without refactoring pipelines or materializing intermediate datasets unnecessarily. The result: a faster, leaner, and more scalable pipeline that minimizes duplication and accelerates analytics and AI delivery to the business
3. Send to Destination: Medallion Architecture & High-Speed Sync
Once data is prepared within Incorta, it can be delivered to Google BigQuery using a medallion architecture, supporting:
- Bronze Layer – raw/CDC data
- Silver Layer – curated, conformed data
- Gold Layer – aggregated, reporting-ready data
Incorta Connect uses a Parquet and Delta Lake–compatible architecture, optimizing integration with data warehouses and lakehouses. It supports high-throughput data delivery—up to one billion rows per minute, with built-in support for:
- Automatic table creation
- Incremental data updates
- Continuous synchronization between Oracle and BigQuery
4. Data Load Orchestration and Observability
Incorta Connect provides robust data orchestration and monitoring capabilities, including:
- DAG-based Load Plans – Define, schedule, and sequence your extraction and delivery workflows using a visual or programmatic interface.
- Lineage Graphs – End-to-end visibility from Oracle PVOs/BIP queries through semantic transformations to BigQuery tables.
- Observability Dashboards – Monitor row volumes, transformation durations, error rates, and delivery latencies in real-time.
These tools allow users to trace every step of the pipeline—from Oracle Cloud to BigQuery—helping quickly identify issues, validate transformations, and ensure data consistency and reliability.
In summary, Incorta Connect provides a fundamentally different approach from traditional ETL pipelines. It combines native Oracle integration, semantic-layer modeling, high-throughput data delivery, and built-in observability into a single, cohesive platform. If you're building a modern data stack that integrates Oracle Cloud and BigQuery, Incorta Connect enables you to do it faster, smarter, and with fewer moving parts.
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