Key Considerations for Converting Legacy ETL to Modern ETL

3 min read
Curated from talend.com →

Since joining Talend in 2017, Sujay has been instrumental in driving strategic initiatives with our enterprise customers. Sujay has a strong background in Modern Data Architecture with a track record of successful implementations of various data initiatives ranging from traditional data warehouses to building modern data lakes, both on-premise and cloud

Recently, there has been a surge in our customers who want to move away from legacy data integration platforms to adopting Talend as their one-stop shop for all their integration needs. Some of the organizations have thousands of legacy ETL jobs to convert to Talend before they are fully operational. The big question that lurks in everyone’s mind is how to get past this hurdle.

To begin with, every organization undergoing such a change needs to focus on three key aspects:

This is where Talend’s Strategic Services can help carve a successful conversion strategy and implementation roadmap for our customers. In the first part of this three-blog series, I will focus on the first aspect of conversion.

Before we dig into it, it’s worthwhile to note a very important point – the architecture of the product itself. Talend is a JAVA code generator and unlike its competitors (where the code is migrated from one environment to the other) Talend actually builds the code and migrates built binaries from one environment to the other. In many organizations, it takes a few sprints to fully acknowledge this fact as the architects and developers are used to the old ways of referring to code migration.

The upside of this architecture is that it helps in enabling a continuous integration environment that was not possible with legacy tools. A complete architecture of Talend’s platform not only includes the product itself, but also includes third-party products such as Jenkins, NEXUS – artifact repository and a source control repository like GIT. Compare this to a JAVA programming environment and you can clearly see the similarities. In short, it is extremely important to understand that Talend works differently and that’s what sets it apart from the rest in the crowd.

Let’s focus on the first aspect, conversion. Assuming that nothing else changes except for the ETL jobs that integrate, cleanse, transform and load the data, it makes it a lucrative opportunity to leverage a conversion tool – something that ingests legacy code and generates Talend code. It is not a good idea to try and replicate the entire business logic of all ETL jobs manually as there will be a great risk of introducing errors leading to prolonged QA cycles.

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Yves Mulkers

Yves Mulkers is the founder of 7wData and a widely followed voice in the data and AI community. He curates the 7wData and AI Beat newsletters, reaching hundreds of thousands of data and AI professionals, and writes on data strategy, analytics, AI, and the evolving data ecosystem.