Domino Data Lab
Domino automates DevOps for data science, so you can spend more time doing research and test more ideas faster. Automatic tracking of work enables reproducibility, reusability, and collaboration.
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MY ROLE
I took this project on a contract-to-hire role for the company’s first office in India. From UX to UI, everything was to be taken care of from a holistic perspective. Though the product came up with an old existing design language ( designed by someone they hired in SF, USA ). But It needed improvements & new feature additions as measured from research & testing through real users during the last couple of months.
THE BIGGEST CHALLENGE
It was the first time that I tackled a data science platform, A field I knew a very little about. Every time I come across a Jira ticket or a research doc, I used to rush to my product manager ( Avinash, really a great guy though :) ) to know the meaning of jargon words shouting on my face. But the team put enough trust on me & gave me enough time to learn. I spent almost a week going through the company’s in-house university course to know every in & out of the product. I got a bit easy start after that but still every day was like a new chapter to my knowledge on how data science really works. That time I came to know about how complex this field is though it may seem all fancy from the Forbes articles.
SECONDARY CHALLENGES
As the product was running in the hands of real customers already & had an existing old design pattern set. Therefore no matter how big UX problems I measured on my end, There was never a quick stop & fix solution. Also due to small team size, The availability of tech team to implement these changes was a core challenge. The team was already very much busy in keeping the platform steady.
As quite visible from few of the screens that you’ll see on this article have difference in the weight iconography & bad colour contrasting. These are the examples of few of the things which remained there for a long time due to many of the secondary challenges & took their time to get replaced with better structure. For example - You can notice the difference in the left navigation bar in some screens from before & after the fixes were being made.
LET’S DIVE INTO WORK
BRAND GUIDELINES
The sales & digital marketing team both were looking for alignment in their pitching content to the customers. Seeing the importance of the matter, I dedicated 2 sprints to set the branding guidelines to be followed by the whole team.
THE IMPACT
This product served as a boost to my understanding of the data science world. The bigger satisfaction factor was to see the implementation of the majority of all these efforts in the actual running product. Seeing the people at giants like Honeywell, Bayer, etc using the features that I contributed to solving the world’s real-life problems is surely a feeling to behold.
Later on, The team decided to talk about the elephant in the room. A better design system for the whole organization, which surely is a case study of its own. You might see it soon in a new post. I really appreciate your time for reading upto this very last word :)