Big Data box and the Black Crayon

SINGAPORE: Ask him what made the founders christen their venture as Crayon, and I Vijay Kumar, CTO, Crayon Data and ex-CTO of Wipro intrigues with a simple and short answer - Because a crayon box is all about imagination and yet without any manuals!

Imagination is certainly the word that is the need of the hour, and acutely so in this space. Big Data is everywhere, in what we generate, consume, in the way IT is sold, bought, leveraged - everywhere. And yet there are these blank spaces around visualization, hardware commoditization, challenges with dark and unstructured data or the various shades of V.

In this interview, I Vijay Kumar fills inside the lines of some question marks and gives us a colorful peek (along with some Mathematics angle about understanding consumers) as he sees it.

A start-up in a big industry. Has it been easy?

If we take conventional model of pushing technology, we know it was capex-driven but now that those barriers have become commoditized there is so much opportunity for start-ups to translate great ideas into reality, without worrying about infrastructure blocks. That's why even big companies are working with start-ups. But yes you have to offer something sharp and precise to the market. We wanted to simplify both the consumer and enterprise side of a so-much-more connected world today.

What's you view of changes happening around MemSQL, VoltDB, HANA etc and their impact on Big Data answers?

Well, the way I see it, most of these are related to infrastructure players and distributed systems. Most of these platforms offer a Big Data infrastructure. As a company or user I don't have to worry where it is running. SAP's work is a layer above that with in-memory database and other tools thrown in. Adoption-wise it will be a good progress. In conventional enterprises, one would be worried about where their data is but that concern is not relevant now with Amazon, Azure and other options.

Would you agree that visualization pieces still need some more work to complete a smooth Big Data cycle?

Visualisation and context does matter. High-end design work is our advantage. We are a design team if you think it that way. What we offer and wok on is an amalgamation of high-end computational science and behaviour science. Because consumer affinity is about behavior and preferences. At the end of the day, the choice engine has to drive the business engine - like market modeling or channel optimisation.

If the proof of the Big Data pudding actually lies in how one wields it, then isn't there a gap between algorithms and human element even now?

There is a difference between a choice engine and the decision-making point. I can give a range of choices and can lead it to the best five out of 100. Single -point answers hence get a different spin here. It's like in Mathematics with large systems, many solutions are non-deterministic but in other areas, we think that if it's not deterministic then it is incorrect. Most of the time even critical solutions have to be done in an approximate way. For wicked problems, solutions are based on how we define the problem, if I can again borrow a leaf from Mathematics. So, with all these social data engines, one does not determine models of single point decisions. It's about how to be close and accurate to the graph as much as you can.

How has the company's progress been, breath and vertical-wise, specially with the recent milestone for being chosen for an innovation award?

Ours is an India-Singapore based big data startup company founded in 2012 and is extremely doing well from winning clients (across verticals like retail, banking, marketing, hospitality) to acquiring funds. Yes, it is great to be shortlisted as one of the finalists at the third edition of annual CODE_nInnovation Awards, the biggest international enterprise startup awards competition, conducted by CeBIT, more so as this year CODE_n received 450 entries from 60 countries, and 50 finalists from 16 countries were shortlisted to make their presentations in Hanover.

We are proud about our offering - Taste Graph, which helps consumers and business to make smarter decisions by simplifying big data and providing relevant and personalised sets of choices. It gives product-wise affinity index and can be very apt for enterprises in blending and deciphering social data as well as enterprise data. Special algorithms therein help in predictive modeling, text mining, application development etc. In terms of verticals, it's too much to boil for a start-up so we will take it one by one, from one sector to another, like hospitality to retail to wealth management and so on.