IKM When Staging Area is Different from the Target Server FAQS

1. What is an Integration Knowledge Module (IKM) in ODI?

•  An Integration Knowledge Module (IKM) is a predefined set of ETL (Extract, Transform, Load) instructions in Oracle Data Integrator (ODI) that defines how data is extracted, transformed, and loaded between the source and target systems. The IKM is responsible for performing the extraction of data, applying transformations, and loading the data into the target datastore based on the defined strategy (Append or Incremental Update).

2. What does a set-oriented SELECT statement do in the IKM process?

•  The set-oriented SELECT statement in an IKM is an SQL query that retrieves data from the source or staging tables. It applies declarative rules to the data (such as filtering, joins, or transformations) and generates a result set, which is a collection of data to be loaded into the target datastore.

3. What are the different data loading strategies in IKM?

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• Append: New data is simply added to the target table without affecting existing records.
• Incremental Update: The data in the target table is updated based on specific criteria, typically to update or overwrite existing records that match the incoming data (e.g., based on a primary key or timestamp).

4. What is a CKM (Check Knowledge Module) in ODI, and why is it important?

•  A CKM is a type of Knowledge Module used in ODI to perform data quality checks before loading data into the target datastore. It ensures the integrity of the data by validating, cleansing, and auditing the data to ensure that only clean and consistent data is loaded. In the architecture described, the absence of a CKM means that there is no built-in mechanism to check data quality before loading.

5. What are the limitations of using IKM for data loading?

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• No CKM for Data Integrity Audit: Since there is no CKM in the process, there are no built-in checks to validate or cleanse the data before it is loaded into the target, which can result in poor data quality or errors being transferred to the target system.
• Potential Performance Issues: Extracting data from the staging area before loading it into the target can lead to performance bottlenecks, especially when dealing with large volumes of data. This additional extraction step can increase the overall time needed to process and load data.

6. How does incremental update work in the IKM process?

•  In the incremental update process, the IKM identifies records in the source data that need to be updated in the target system. Typically, this is based on a matching criterion such as primary key or a timestamp that indicates which records have changed. The IKM then updates the existing records in the target with the new or modified data from the source.

7. Can IKM be used for real-time data processing?

•  The IKM process in its typical usage is batch-oriented and works well for scheduled ETL jobs. For real-time or near-real-time processing, you may need to use other methods or Knowledge Modules designed specifically for real-time data integration, such as those involving change data capture (CDC) or integration with messaging systems.

8. What happens if there are errors in the data during the IKM process?

•  Since the described architecture does not include a CKM, errors in the data (such as missing or inconsistent records) are not caught before loading. This could result in incorrect or incomplete data being loaded into the target system. To mitigate this, additional error handling or cleansing steps might need to be implemented outside of the IKM process.

9. How can performance issues be addressed in the IKM process?

•  Performance issues can be minimized by optimizing the SQL queries used in the set-oriented SELECT statement, using indexes on source and target tables, or partitioning large tables. Additionally, parallel processing or batching techniques can be employed to speed up data extraction and loading. In some cases, tuning the database or adjusting the data flow logic can improve performance.

10. Can IKM be customized to suit specific requirements?

•  Yes, IKM can be customized to some extent. While IKMs come with predefined functionalities, you can extend or modify them by creating custom Knowledge Modules (KM) to meet your specific needs. This includes adding extra data validation checks, adjusting the loading logic, or optimizing performance for specific scenarios.

11. What should I do if I need to perform data quality checks before loading?

•  If you need to perform data quality checks, you should consider using a CKM in your process. This will allow you to validate and clean the data before it is loaded into the target system, ensuring the integrity and consistency of the data.