Exploring Data Transformation Strategies

Liferay DXP offers flexibility in how you store, transform, and migrate data. Especially with interactions between interconnected systems, transformation of data from one structure to another may be required. Organizations frequently leverage Extract, Transform, Load (ETL) tools to move data between systems. ETL processes transform data from its source format to the desired destination format, ensuring data quality and consistency across different applications.

Equipped with a better understanding of data migration, Clarity will use batch client extensions to migrate JSON data between environments, transforming some data before import. Here, you’ll learn about techniques for transforming data in Liferay with client extensions.

Understanding Data Transformation with Liferay

Backend client extensions provide a flexible way to integrate data, whether through custom ETL pipelines, scheduled tasks, or real-time integration. While not a direct ETL tool, client extensions can transform data and build custom pipelines by leveraging Liferay’s tools and APIs.

Liferay offers two primary methods for transforming and loading data through backend client extensions:

• Batch Client Extensions: Batch provides a simple mechanism for integrating with ETL processes for result storage. Entries can be transformed during import using the fieldNameMappingMap property.
• Microservice Client Extensions: Well-suited for complex or real-time integration scenarios, these enable you to leverage custom microservices to transform data. You’ll learn more about microservice client extensions in Module 2.

Implementing Clarity’s Transformation Plans

When populating data for their distributor management app, Clarity wants to augment their newly created submissions with historical application data from a legacy system. They possess a JSON file containing this legacy data, which will be transformed and imported into Liferay. As Clarity doesn’t require real-time integration for this data, they’ll leverage a batch client extension to transform its entries to the appropriate data structure.

Best Practices for Transforming Data with Client Extensions

Whether using batch or microservice client extensions to transform data, consider these best practices:

• Identify Data Sources and Targets: Clearly define the source systems (e.g., databases, APIs, files) and the target Liferay data structures (e.g., content types, user groups).
• Clean and Validate External Data: Implement data cleansing and standardization techniques to remove errors, inconsistencies, and duplicates from external data, normalize data to a consistent format, and map source data to target Liferay data structures.
• Transform Data Appropriately: When importing data from an external system, leverage the fieldNameMappingMap field when needed to transform data to conform to Liferay's data structures.
• Consider Data Volume and Update Frequency: Carefully consider the migrated data’s volume and required update frequency to determine the optimal transformation approach (batch vs. real-time). When importing data in bulk, leverage Liferay's headless REST APIs or batch jobs for processing. For real-time integration, consider instead using webhooks, messaging systems, or streaming technologies with microservice client extensions.
• Intentionally Optimize Performance: Leverage caching, batching, and asynchronous processing to optimize database queries and minimize network traffic. Implement monitoring tools and thoroughly test in lower environments to track performance and identify issues.
• Maintain Data Security Measures: Implement authentication and authorization mechanisms to protect sensitive data, ensuring that credentials and API keys are securely stored.

Conclusion

Leveraging Liferay’s tools and APIs, you can implement complex ETL procedures using the batch engine. Liferay offers two primary methods for transforming data through backend client extensions. Batch client extensions provide a simple mechanism for integrating with ETL processes for result storage. Microservice client extensions leveraging custom microservices and excel in complex data transformations. Next, you’ll transform legacy data from Clarity’s distributor management app and import it into Liferay using a batch client extension.