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The Chronicles of ETL Data Transformation: A Day in the Life of a Product Manager

How a simple home task changed the way we look at data transformation.

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On a beautiful sunny day in Tel Aviv, I had the privilege of hanging my own shelves in my new apartment. 

As I looked in front of me at this seemingly impossible task, as I own no tools, not even a drill, it dawned on me that I had 2 options: buy a drill or call a handyman.

As a product manager by nature and by job title, I did some research and determined the cost of a handyman for one hour was approximately the cost of purchasing a good drill. But what is a good drill? What should it cost? What features do I need? 

It was at that point I stepped back and started counting exactly how many holes I required because ultimately – that was what I was looking for. 

Will I use my new tool, my new drill frequently? Do I want to own a drill? Do I have a place to store it? Do I need it for other purposes? The answers to these questions will tell me what I need to know but again, all I really need right now is a hole in my wall. 

In my view, it’s the exact same with data. 

Life seems to have many of these conundrums. It starts with a drill and a hole and next it’s should I use this common data tool or find some all-encompassing solution?   

Most companies today engrain ETL (Extract, Transform, Load) solutions and capabilities in their core. They have numerous disparate data sources, even more destinations, and processes that not even they can explain. No matter if we are trying to determine whether to buy a drill or pay a handyman, these problems are one and the same, in that the same logic can be applied.    

The drill or the many current ETL processes today are overkill, requiring investments in time and money when the alternative will get you from point A to point B, without the commitment.

At the end of the day, we just want to put our hole in the wall. 

In ETL this means we just want something easy. Something that snaps into our existing infrastructure, with complete observability, complete control, an easy interface, and no strings attached.  

We want templates with speedy onboarding to production time, modular building blocks with advanced configurations that can be chosen or discarded as needed, and the ability to add the missing piece to our pipeline without a commitment. 

So how does data transformation play into this? 

Taking my putting a hole-in-the-wall analogy and applying it to the data world – we developed a simple solution to those all-too-common data transformation issues every company seems to deal with. 

Working with and combining data from any source, we offer one clean, clear, and easy interface to merge everything together. With easy data transformation configurations engrained into the system itself, we created the simple tool you’ve always wanted. 

A tool that snaps into any flow, with complete observability of inputs and outputs showing your data schema before and after implementation. A filter module that allows for set conditions allowing you to remove or store data as required. The ability to forward data to where it is needed most, oh, and of course, a user-friendly interface anyone can use. 

It makes sense to me and you should try it for yourself. Test out our interactive demo and let me know what you think. 

By the way, my neighbor is a DIY fanatic so he actually ended up helping me with the shelves.

Lessons learned, maybe an easy-to-use tool is all you really need, and sometimes it’s smart to know your neighbors.

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