This article is a continuation of our previous article on unlocking legacy Oracle E-Business Suite data for Oracle Fusion Cloud. In that article, we explored the strategic importance and foundational approaches to integrating Oracle E-Business Suite data. In this article, we shift the focus to a powerful, next-generation approach: consolidating Oracle Fusion AI Data Platform and E-Business Suite data using Oracle AI Data Platform.
Introduction to Oracle AI Data Platform
Oracle AI Data Platform represents Oracle’s latest commitment to helping organizations realize the full value of their data. Launched to enable seamless data integration, governance, and AI and ML at scale, this cloud-native platform provides:
- A unified lakehouse architecture for both structured and unstructured data.
- Oracle AI Data Platform supports open formats, namely Iceberg and Delta Lake, for managing data in Oracle Cloud Infrastructure Object Storage.
- Native ingestion and transformation services.
- Built-in governance, security, and lineage tracking.
- Direct enablement of analytics and machine learning use cases.
By centralizing data assets and AI and ML tools, Oracle AI Data Platform accelerates the path from raw data to actionable intelligence.
Use case
The central focus of our solution is leveraging Oracle AI Data Platform to seamlessly integrate financial data from Oracle Fusion AI Data Platform, Oracle E-Business Suite, and Oracle Fusion Cloud Enterprise Performance Management. By integrating these sources, organizations can compare actual revenue and profitability KPIs from Oracle Fusion Applications and Oracle E-Business Suite with planning data from Oracle Fusion Cloud Enterprise Performance Management in a unified view. This integration breaks down silos between transactional and planning systems, improving financial transparency and insight. Oracle AI Data Platform provides secure data pipelines, governance, and AI-powered analytics, helping harmonize financial KPIs across systems. Ultimately, this empowers organizations to make more informed, data-driven decisions that enhance both strategic planning and operational effectiveness.
Solution approach
Discovery and source assessment
Identify core datasets from Oracle Fusion AI Data Platform analytics models and relevant Oracle E-Business Suite modules needed for unified analytics or AI.
Data ingestion
Medallion architecture is used to logically organize data in the lake house, with the goal of incrementally and progressively improving the structure and quality of data as it flows through each layer of the architecture (from bronze, silver, and gold layer tables).
- Oracle E-Business Suite: Data from Oracle E-Business Suite tables are brought into Oracle AI Data Platform as delta tables in the bronze layer. These are refined through the silver and gold layers to enable reporting and machine learning use cases.
- Oracle Fusion Applications: Oracle Fusion AI Data Platform supports data sharing with external data stores alongside Oracle AI Autonomous Lakehouse, enabling customers to enhance analytics by integrating Oracle Fusion AI Data Platform data with external sources. This capability allows simultaneous sharing of full or incremental datasets with both Oracle Fusion AI Data Platform and external platforms. Oracle AI Data Platform serves as one such external data store, leveraging this feature to access curated tables shared from Oracle Fusion AI Data Platform.
Data transformation and harmonization
For consolidated reporting across Oracle E-Business Suite and Fusion, historical closed transactions from Oracle E-Business Suite (gold layer delta tables) are combined with current transactions from Fusion (Fusion AI Data Platform delta tables) into a single fact table. E-Business Suite data is joined with customer-provided master data cross-reference mapping tables to align legacy E-Business Suite values with their corresponding Fusion Applications configurations. This mapping ensures consistency and integrity in the consolidated fact table, enabling unified analytics across both platforms and supporting seamless migration from Oracle E-Business Suite to Fusion Applications.
AI, analytics, and consumption
The consolidated reporting data, along with additional data points required for analytics, is ingested into the Oracle Autonomous AI Data Lakehouse. Oracle Analytics Cloud is then utilized to create interactive visualizations and reports on this unified dataset. The dashboard displays Actuals compared to Budget and Forecast, along with variance analysis, providing a clear view of financial performance. Users can filter data by source—either Fusion Applications or E-Business Suite, chart of account segments and period. This supports more informed decision-making and streamlines financial review processes.
Note: Oracle Analytics Cloud offers a native, built-in connector for Oracle AI Data Platform, enabling seamless integration for analytics and data visualization. You can create datasets directly on delta tables within Oracle AI Data Platform and use them for analytics. This option can also be utilized for ad-hoc analysis, providing an alternative to the traditional approach of modelling data with Oracle Analytics Cloud Semantic Modeler.
The data stored in Oracle AI Data Platform) can further support advanced AI and ML initiatives. Oracle Data Platform offers an integrated suite for building, training, and deploying machine learning models, encompassing prebuilt Oracle Cloud Infrastructure AI Services, a robust data science service, in-database machine learning capabilities, and the MySQL HeatWave AutoML engine. This architecture ensures a streamlined, end-to-end solution for both analytics and AI and ML-driven insights.
Note
To ensure the consolidated reporting solution comprehensively addresses all business requirements, it‘s essential to incorporate the key considerations outlined in the preceding article – https://blogs.oracle.com/analytics/post/unlocking-legacy-ebs-data-for-oracle-fusion-cloud.
Adhering to these guidelines will promote accuracy, consistency, and reliability in enterprise reporting.
Architecture
A typical architecture for consolidating Oracle Fusion AI Data Platform and Oracle E-Business Suite data using Oracle AI Data Platform looks like this:
The technology stack includes Oracle Fusion AI Data Platform, E-Business Suite, and Oracle Cloud Infrastructure Object Storage .
Conclusion
As a follow-up to our previous article on integrating legacy Oracle E-Business Suite data, this article demonstrates how organizations can dramatically enhance their analytics and AI and ML capabilities by consolidating Oracle Fusion AI Data Platform and Oracle E-Business Suite data in Oracle AI Data Platform. With its robust integration, governance, and scalability, Oracle AI Data Platform stands as the ideal foundation for data-driven innovation. Stay tuned for future articles where we’ll share implementation patterns, customer stories, and best practices for maximizing value from your Oracle data estate.
Call to Action
• Now that you’ve read this article, try it yourself, and let us know your results in the Oracle Analytics Community, where you can also ask questions and post ideas.
• Find out more about Oracle Fusion AI Data Platform in Oracle Help Center.
• For more information on these solution approaches, reach out to the CSS Innovation Studio team at – css_innovation_data-analytics-studio_in_grp@oracle.com