How do you create reusable and modular ETL processes?

When looking at applying a SOA/Microservices approach for ETL processes It would be prudent to look at the required outcome or required state of the dataset in your architectures end-point and not at what is "common" at the "E" stage of ETL. When using a mature true Enterprise ETL tool this may be an option to a certain degree as there is a large amount of hard earned logic and code behind the seemingly simple steps. A basic query of Select * from X Table Where Date / Time / "Control" value is X will have entirely different variables required to be effective , optomised and indexed for each source system. "E" is a challenge for commonality for a CRM vs ERP VS 3PL for example. Context is Key! Know your data & keep your outcome in focus.

Creating a shared library of common ETL functions is a step towards establishing a standard across the ETL processes, fostering code reusability and consistency. Additionally, having a version control system for this shared library can ensure traceability and ease of updates, allowing for a structured way to introduce and roll back changes.

Leveraging frameworks like Apache Airflow or tools like Talend can indeed accelerate the development of modular ETL processes. They not only abstract away some of the complexities but also provide a community-driven approach to common challenges faced in ETL processes, enriching your ETL solutions with best practices from industry experts.

Modularizing is important: each module should represent a funcionality that may be reused in different pipelines. If needed, parameterizing is a strategy for flexibility, configurating variables that allows the use of the code in differnte contexts instead of hard coding. Modules are organized by functions (extraction, cleansing, transformation etc.), that must be well documented and versioned to be able to collaborate as a team. The goal is to create a framework that is flexible and robust and reusable, saving development time and improvind data quality.

Breaking down ETL processes into independent, configurable modules promotes a plug-and-play architecture. This modularity paired with a well-thought-out configuration management system can significantly ease the adaptation of ETL processes to changing business requirements, creating a long-lasting and flexible ETL solution.

Implementing automated testing as part of a CI/CD pipeline can ensure the reliability of the ETL processes, while comprehensive documentation facilitates knowledge transfer, enabling team members to understand, use, and extend existing ETL processes efficiently.

Break down the ETL process into logical components that perform specific functions such extracting data from sources, cleansing/transforming data, loading data into targets, etc. Encapsulate each component in a separate module. Create generalized modules that can work with different data sources or targets, and pass configuration/credentials as parameters. Centralize common functionality like logging, error handling, and utilities into shared libraries. Design modules to be stateless - they should not depend on external state or prior execution. Implement orchestration and workflows to sequence and coordinate modules using workflow engines. Containerize modules to standardize and deploy them across environments!

A culture of collaboration and continuous feedback among the data engineers, data analysts, and business users can further hone the reusability and modularity of ETL processes. Real-world feedback from different stakeholders can unveil new perspectives, driving enhancements that make the ETL processes more robust and aligned with business needs.