Oracle Data Integrator (ODI) utilizes an ELT (Extract, Load, Transform) architecture by shifting the processing burden away from a centralized middle-tier server and instead pushing transformation logic directly to the source and target databases.
The sources highlight several key ways ODI implements this architecture:
1. Pushing Logic to the Data
In a traditional ETL model, transformations happen in a separate engine. In contrast, ODI’s ELT approach leverages the inherent processing power of the databases (such as Oracle EBS and Oracle ADW) where the data already resides. This is particularly effective when the target is an Oracle Autonomous Data Warehouse (ADW), as it allows the system to utilize ADW's auto-scaling and automatic optimization capabilities for complex transformations at scale.
2. Knowledge Modules (KMs)
The "how" of the ELT process is handled by Knowledge Modules, which are pre-built, modular code templates. These modules allow ODI to execute specialized tasks:
• LKM (Load Knowledge Modules): Used for extracting data from source systems and moving it to the staging area.
• IKM (Integration Knowledge Modules): Used to perform the actual transformations and load data into the final dimensional models.
• CKM (Check Knowledge Modules): Used to validate data quality and ensure consistency during the load.
3. Declarative Design
ODI uses a declarative design pattern, which separates the business rules (the "what" of the transformation) from the physical implementation (the "how" it is executed). This allows developers to define the data mappings once, while ODI generates the optimized SQL or PL/SQL code required to execute those transformations within the database environments.
4. Orchestration and Consistency
ODI manages the ELT lifecycle through Load Plans and dependency-aware pipelines. This orchestration ensures a strict execution contract:
• Data is first moved from EBS to the Staging Layer.
• Downstream transformations to the Dimensional Layer only trigger once dependencies are met and data integrity is validated.
• If a transformation fails, ODI is designed to abort the integration and roll back partial results, ensuring the dimensional tables never exist in an "in-between" or inconsistent state.
5. Metadata Management
To handle evolving data structures, ODI uses model reversal and metadata management. This allows the ELT process to detect and adapt to schema changes in the Oracle EBS source system, ensuring that the transformation logic remains synchronized with the operational data.
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