Nov 25, 2024

Options for Replicating Oracle Fusion Cloud ERP Data into Third-Party Data Warehouses

Organizations planning to replicate Oracle Fusion ERP (Oracle Fusion Cloud Applications) data into third-party data warehouses, such as Snowflake, Databricks, Microsoft Azure ADSL, Amazon Web Services Redshift etc., have various options available. Each solution provides distinct advantages, catering to different business requirements and technical environments. This discussion will focus on two main approaches: Oracle’s multi-step replication solution and Orbit Analytics’ direct replication solution.

Oracle’s multi-step replication solution:

Oracle offers a comprehensive, multi-step approach for transferring data from Oracle Fusion ERP to third-party data warehouses, utilizing Oracle Data Integrator (ODI) and Oracle GoldenGate. For more details, refer to Oracle’s documentation

Oracle Data Integrator (ODI) and Oracle GoldenGate

Oracle recommends a two-step ODI process for initial data extraction, transformation, and loading into Oracle Autonomous Data Warehouse (ADW), followed by Oracle GoldenGate to replicate this data to third-party data warehouses.

Step 1: Oracle Data Integrator (ODI)

Description Oracle Data Integrator is a powerful ETL tool designed to handle complex data transformations and integration tasks. Process
  • Extraction: Data is extracted from Oracle Fusion ERP.
  • Transformation: Data is transformed according to business requirements.
  • Loading: Transformed data is loaded into Oracle Autonomous Data Warehouse (ADW).
  • Benefits: 
    • Comprehensive ETL Capabilities: Robust data transformation and integration functionalities.
    • Seamless Oracle Integration: Secured integration with Oracle products ensures efficient data flow.
    • Scalability: Suitable for large-scale data handling and processing.

Step 2: Oracle GoldenGate

Description:Oracle GoldenGate enables real-time data replication from Oracle ADW to various third-party data warehouses like Snowflake, Azure, and AWS Process:
  • Capture: Real-time data capture from Oracle ADW.
  • Delivery: Data is delivered to target third-party data warehouses.
  • Benefits:
    • Real-Time Replication: Ensures timely data availability across systems for real-time analytics.
    • High Reliability: Enables high availability and fault tolerance.
    • Flexible Integration: Supports multiple data sources and targets, allowing versatile data integration solutions.

Orbit Analytics’ direct replication solution:

Orbit Analytics provides a plug and play streamlined solution for replicating data directly from Oracle Fusion Applicatuons to third-party data warehouses such as Snowflake, Oracle Autonomous Data Warehouse (ADW), Oracle Database, Amazon Web Services Redshift, MySQL, SQL Server, and more. Description:Orbit Analytics offers pre-built connectors and automated processes to transfer data directly from Oracle Fusion Applications like ERP, HCM, SCM, EPM to third-party data cloud and on-premise warehouses. Process:
  • Direct Extraction and Loading from Oracle Fusion Cloud Applications: Data is extracted from Oracle Fusion Cloud Applications like ERP, HCM, SCM and loaded directly into third-party data warehouses.
  • Benefits: 
    • Simplicity and Ease of Use: Minimal configuration is required, making setup and management straightforward.
    • Cost-Effective: Reduces the need for multiple tools and stages, lowering operational and licensing costs.
    • Rapid Deployment: Enables quick implementation and deployment, helps organizations to start leveraging their data sooner.
    • Optimized Performance: Customized for specific use cases with pre-built connectors, ensuring efficient data replication.
orbits-oracle-fusion-cloud-data-pipelines-for-redshift

Illustration of Orbit Analytics’ Data Replication

Comparison of the Two Approaches
  • Direct Extraction and Loading from Oracle Fusion Cloud Applications: Data is extracted from Oracle Fusion Cloud Applications like ERP, HCM, SCM and loaded directly into third-party data warehouses.
  • Benefits: 
    • Simplicity and Ease of Use: Minimal configuration is required, making setup and management straightforward.
    • Cost-Effective: Reduces the need for multiple tools and stages, lowering operational and licensing costs.
    • Rapid Deployment: Enables quick implementation and deployment, helps organizations to start leveraging their data sooner.
    • Optimized Performance: Customized for specific use cases with pre-built connectors, ensuring efficient data replication.
Oracle Orbit Analytics
Data Movement Utilizes a multi-step approach (ODI to ADW to GoldenGate) that ensures comprehensive ETL capabilities and robust, real-time data replication. Directly moves data from Oracle Fusion Cloud Applications like ERP, HCM, SCM  to third-party warehouses, simplifying the process and enabling rapid deployment.
Integration Offers seamless integration within the Oracle ecosystem, suitable for enterprises with significant Oracle investments. Prioritizes ease of use and rapid deployment with direct integration, ideal for businesses seeking straightforward solutions.
Performance and Scalability Delivers high performance and scalability, suitable for large-scale  applications. Ideal for both smaller-scale and large scale applications replication needs, focusing on cost-effectiveness and user-friendliness.

Conclusion

Choosing the right solution for replicating Oracle Fusion ERP data into third-party data warehouses depends on the organization’s specific needs:
  • Oracle’s Solution: Suitable for enterprises requiring comprehensive ETL capabilities and integration within the Oracle ecosystem. Best suited for large-scale enterprises. Please refer https://www.orbitanalytics.com/orbit-data-pipeline/ for more information.
  • Orbit’s Solution: Ideal for organizations seeking a direct replication of data into the data warehouse, cost-effective, and user-friendly solution. Ideal for Enterprises that prioritize rapid deployment and straightforward integration.
By evaluating these options, organizations can select the solution that best fits their technical requirements, budget, and overall data strategy.

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