I’ve been working on automating some data pipelines lately, and I keep running into the same wall with other tools. Every time I need to do something like array manipulation or aggregate data in a specific way, I end up creating these massive chains of transformation steps. It gets messy fast, and honestly, it feels inefficient.
I read somewhere that custom code modules can help with this, but I’m not sure if that’s overkill for what I’m doing. The main challenge is that I’m dealing with fairly large datasets that need transformations before they hit our CRM. Right now I’m doing it all through predefined modules, but it’s taking forever to set up and maintain.
Does anyone here just write custom logic directly in their workflows? How do you approach it without needing to be a full-time developer? What’s your workflow look like when you’re handling this kind of data complexity?
Custom code is exactly what you need here. I was in the same spot a few months back, dealing with complex array manipulations that would’ve required me to chain 15+ steps together.
What changed everything for me was using JavaScript modules that run directly in the workflow. You get access to NPM packages, which opens up a ton of possibilities. I can now handle string manipulation, data aggregation, filtering, sorting, and statistical analysis all in one step.
The best part? If you’re not comfortable writing code from scratch, there’s an AI assistant built in. You just describe what you want to do, and it generates the code for you. Saved me hours on debugging.
Check it out: https://latenode.com
You’re hitting on something a lot of people struggle with. The predefined module approach works fine for simple stuff, but when you need real flexibility, it falls apart.
I started writing custom code about six months ago, and honestly, the learning curve wasn’t as steep as I expected. The key thing is that you don’t need to be perfect. You can test as you go, and if something breaks, you can see exactly where.
One thing that helped me was starting small. Pick one transformation that’s giving you the most pain, move it into a custom code block, and go from there. Once you see how much cleaner it makes your workflow, you’ll want to do more.
Also, having version control and the ability to restart from history is huge. Means you can experiment without fear.
I dealt with this exact problem when handling customer data import pipelines. The real issue with chaining modules is that each step adds latency and cost, especially when working with large datasets. Moving to custom code solved that problem entirely.
What I found most effective was consolidating related transformations into single code blocks. For example, instead of five separate filtering and mapping steps, I’d write one function that does all of it at once. The performance improvement alone made it worth learning JavaScript basics.
The NPM package access is also underrated. I ended up using libraries for things like date manipulation and data validation that would’ve taken forever to build manually. Start simple and build from there.
yup, custom code is the way. Wrote a function handling array transforms in seconds instead of 10+ steps. npm packages help alot too. way cleaner than chaining mods.
Use JavaScript modules with NPM packages. One code block replaces 10+ transformation steps.
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