Interview: Santhosh Adayikkoth, CEO, BigInfo Labs on Data Relevance and Intel Partnership

We discuss BigInfo Labs, the concept of "Data Relevance" in Big Data, experience of partnership with Intel, and BigInfo Labs' strategy for competitive differentiation.

Santhosh AdayikkothSanthosh Adayikkoth defines and owns BigInfo Labs' vision, strategy & execution. He has over 20 years of experience in exploring new technology, solutions, markets and in incubating new service lines and converting them into profitable practices in large IT corporations

As a thought leader in his area Santhosh spoke at various events including Council of Scientific and Industrial Research) India meet on Collaborative Innovation in the area of Drug Discovery, Search Summit at Orlando FL - Microsoft FAST, SAP Summit at Mumbai (Solutions for RETL and CPG).

Santhosh has co-authored a book – “Collaborative Computational Technologies for Biomedical Research (Wiley Series on Technologies for the Pharmaceutical Industry)” – along with the leaders from CSIR.

Here is my interview with him:

Anmol Rajpurohit: Q1. BigInfo Labs is a data relevance company. How do you define "data relevance"? Why do you think it is very important in the world of Data Science?

BigInfo LabsSanthosh Adayikkoth: Often, whenever analytics is discussed the talk eventually turns to insights and the value gained from it. It is assumed that the underlying information being inquired is apt for drawing these inferences. Such an assumption has direct impact on outcomes, accuracy and eventually cost when it comes to Big Data. Data Relevance in this scenario is just that. It is the quality of information being inquired so as to yield the most actionable insights. This is easier said than done.

Relevant data is not just a choice subset of the underlying information pool (or ocean in the case of Big Data!), but data that has been processed and extracted so as to yield the most pertinent and actionable insights within an inspection context. Context is everything and poses the greatest challenge in carrying out such processing.  Capability to 'Attend to the Relevant' therefore converts your Big Data problem into something of manageable proportions and makes the analysis effective and efficient.

BigInfo Labs' technology innovations are targeted at precisely this problem.

AR: Q2. What were your aspirations behind partnership with Intel? How has the partnership experience been so far?

SA: Our Intel partnership has multiple objectives really. First of all, they have a great vision and a platform to match it with the Intel Hadoop. The recent changes in regards to the merging of Intel Hadoop with Cloudera further strengthen the platform. Several of our innovations Intel Clouderain the space of Big Data analysis & processing directly benefit from their contributions to the Hadoop ecosystem. So in a  way, we can have a two-way conversation about how to make the platform better for enterprise adoption. Secondly, we greatly benefit from the reach and install base of Intel. We’d like as many customers as possible to benefit from our solutions. We know several clients who have Big Data initiatives that are in their nascence. They have deployed either Intel / CDH platforms and are in the process of identifying or addressing suitable business problems. Our targeted vertical solutions can easily be deployed in such scenarios. This helps clients to reap maximum benefits from their Intel investments.

Hence, our partnership with Intel is very strategic and to use the clichéd term, a 360 degree relationship in reality. It has been very effective so far. We have enjoyed working closely with both their product/platform and business development teams, sharing keen insights into several domain problems and together formulating a strong success message for our enterprise customers.

AR: Q3. Today, there is a plethora of Big Data startups with the number consistently increasing. What distinguishes BigInfo Labs from the competition? What do you consider as the most important factors of competition?

SA: That’s very true. Infact the answer to that question was very important even before we started on the journey that eventually resulted in the formation of BigInfo Labs. The opportunity was obvious and I won’t belabor that point. There are some really cool technology innovations out there for handling gargantuan volumes of information in any and all forms; innovations on data & computationally intensive in-memory processing, innovations for handling connected data, innovations on high speed computing in general like making supercomputing accessible to enterprises, scaling traditional information management technologies and making them big data ready and so-on. There are companies out there who are really doing wonderful work and making an enormous difference to their customers through large scale unstructured data analytics, finding new ways to tap into the social media data for businesses, using publicly available information aided by more open government policies for the general welfare of the masses and so on. So, definitely a very exciting & happening space.

What we see across this spectrum is that organizations are no longer seeing Big Data as a new thing and something they have to get into. That point has been made. It is now, like any other IT endeavor.

Business ValueOne has to justify business value from the initiatives and not just talk about the potential alone. To this end, there is definitely a dearth of true end to end business solutions, particularly those targeting the data within the enterprise.

Big Data innovations, including those of BigInfo Labs allow us to break down information barriers within an enterprise like never before to solve genuine business problems spanning different domains. Our innovations synergistically embrace other Big Data innovations but have their own really cool ways  of making those insight nuggets available to business users for specific business problems. Our innovations allow organizations to leverage their existing information management & analytics investments but answer a new class of questions. Questions which can even be discovered by business users using our solutions. I guess this attention to enterprise business applications differentiates us and our offerings from the excellent companies that are out there.

Additionally, from day one we had been investing in our patent pending Big Data Platform. So rather than being a plain old user of a new technology, we have been developing innovative techniques to handle Big Data. We did not hesitate to take a few steps back, go back to the first principles and see if there is a better way to address this problem of abundance. This curiosity and drive to innovate is also a differentiator.

I think these are the constructs which will be the most important factor for competition. Sure in the short term there will be a really crowded market place. But we believe that only those with a clear vision on specific business problems and those that have truly ground breaking technology innovations will consolidate & emerge successful in the long term.

Second and last part of the interview: Santhosh on Big Data perception and learning Big Data skills