UPDATED 18:39 EST / FEBRUARY 26 2014

Context computing : Inhi Cho Suh is excited about real-time Big Data | #IBMpulse

Inhi Cho Suh IBM What’s got Inhi Cho Suh’s attention? Real-time and context computing. Big Data is about enabling everyone. It’s about the democratization of data, giving all the ability to insights and not require you to have a Ph.D or to be a data scientist just to understand the data.

This week at IBM Pulse 2014, VP GM Big Data & Integration Inhi Cho Suh is among the most memorable of our #techathletes on theCUBE. Suh joined our co-hosts John Furrier, Founder of SiliconANGLE and Dave Vellante, Co-Founder of Wikibon to discuss IBM and Big Data.

Setting the Big Data table

Big Data is still in its infancy. But the industry’s bleeding-edge is aging with two years of hype behind it, so products and services are starting to catch up. Clients are recognizing that data is transformative for their organizations. With that comes a bevy of new opportunities and new business models. The consumer on the personal side is seeing a radical shift in the user experience, and they are now bringing that expectation from their personal life into their professional life. The cloud is housing all of those expectations, driven by social demand, and it is making both the connected consumer and connected business more and more actionable in real-time, and transparent. Suh says,

“Clouds are more transformative not just from a delivery standpoint, but also fundamentally from expectation which gets into social, which is really the engagement side. People are all about on demand. The days of just being able to do e-mail is a little bit passé. People want to be on text communicating in real time, in the personas they represent. So its not just their work personas, but lets say your personal hobbies, they want to be interactive with relevant in real-time and context.”


IBM marries insights and behavior traits

Facebook’s recent acquisition of WhatsApp for $19 billion, with another $3 billion in retention, speaks directly to this concept of consumers bringing those expectations into the business. Earlier this week on theCUBE SoftLayer CEO Lance Crosby said, “Facebook is disrupting a $100 billion telecommunications market.”

But if this is where the market is headed, why is the telecom industry so far behind and always late to the party? Sheer volume. The telecom industry, in Suh’s opinion, has a big challenge: “find how they can do it more effective and an optimized and predictive way, that is the opportunity.”

IBM’s acquisition of NOW Factory this past October aligns it to be a big player in Big Data for the $100 billion telecom world. With IBM, NOW Factory is focused on making more proactive call centers, drilling down to individual level of user access and understanding where the quality of service issues are on that user to user basis.

Suh gives the example of a recent conversation she had with a couple of IBM’s clients, one that is in banking on Europe and another in insurance based in the U.S.:

“Customer retention is huge for revenue and profit – revenue from cross-sale of products, profit the longer you can retain the products the better. Human logic or expectation of ‘how to retain a client what people think they need to do’ maybe you get better products, higher level of discounts. One of the human behavior traits we discovered, is if you actually lower the price points (change the rate, change the available prices for certain accounts and products) it actually causes the customer to leave. The reason – after it hits a certain threshold, what happens is human nature says ‘oh, I might be attractive to other vendors,’ so they go start looking.”

Suh even mentions that IBM has recently look at online dating surveys and information that’s captured from online relationships, in her words, “because what people say they are going to do and what people actually ending up doing are sometimes drastically different.”

Suh and her team are marrying that kind of insight with more business information to really understand human behavior traits. Vellante added that this was a great example of non-intuitive things that can be found inside Big Data. Suh is very bullish on marrying industries perspectives about people, profiles, identities to get a more comprehensive understanding that one wouldn’t have necessarily thought of doing before.

Present and accounted for with Cloudant

Broadening its definition of the cloud, IBM is moving beyond Infrastructure-as-a-Service (IaaS) as part of an ambitious push to capture a larger slice of the burgeoning enterprise cloud market. When asked about what she was most excited about at the IBM Pulse 2014 event, Suh responds by saying Cloudant.

“It’s about being present in the ways in which clients are actually developing the next generation of applications,” Suh notes. “Especially for mobile applications and what they’re doing in the cloud. It’s such a unique business model (referring to Cloudant).”

Cloudant is a database as a service, with NoSQL. Cloudant has actually been a strategic partner with IBM on Soft Layer, so the companies know each other very well.

“Innovations that are happening in the data world spanning the spectrum of NoSQL, to not only SQL, to SQL is all about clients wanting to both leverage new capabilities that allow application agility and flexibility. They want capabilities enabling higher performance and speed and cost reduction.”

A pattern is emerging too, according to Suh. “Even in the Hadoop world there is a big movement toward being able to apply SQL. There aren’t enough MapReduce programmers,” she says. “And part of the value of NoSQL in areas like Cloudant is about allowing application developers the ability to write and quickly program things that they need without necessarily having to have the number of traditional resources.”

This is all about speed. Speed in terms of data, speed in terms of application agility.

Big Match: Humanization + fusion of data

When asked by Furrier to talk about both the humanization of Big Data and the fusion of Big data, Suh gave a tangible example.

“Most clients have an enterprise warehouse of some sort or a transactional system that says, ‘You are in fact John, you are in fact Dave,’ but you may have 50 different social handles that are very different than an enterprise id that says name, address, e-mail,” Suh explains. “So we have a capability called Big Match, which takes capabilities like probabilistic matching, traditionally found in master data management capabilities and enabled that for you to apply with a higher degree of confidence to resolve entities and ID’s of people even when their social ID’s may not be apparent they are in fact their information.”

Dave cleans that thought up into something we can all immediately understand: so you can infer fuzzy information more about that individual.

“With a high degree of probability,” says Suh. This is not news, as there are a lot of players both big and small trying to work on that problem, its a hard problem.

Suh came carrying more gifts, telling Furrier “I’m going to give you a data point.” IBM ran an internal test and they were able to identify 10 million profiles in 1 second using Hadoop. That’s at the scale of several times faster than what you’d expect from traditional database relational management systems but with a degree of precision too.

IBM just delivered Big Match this past 4th quarter and Suh is really excited for what Big Match can bring to the table as it relates to Context Computing. It’s a term IBM uses internally that describes an incremental programming thought that says every piece of data could cause you to step back and relook at your assumptions of the data. Context computing is assumption-proof computing.

Context and agile computing in real-time

Suh sums up her goals in Big Data as such: shifting towards agile analytics that offer continuous and actionable insight — in the middle of a process, in real-time, in context. So analysis of data in real-time in context in the middle of an process that allows you to see analytics of every step of the way. No big deal. (ha!) She sees the biggest current areas of adoption being data monetization and privacy, as more companies are being proactive about privacy than one might have thought. Real products and methods of privacy, not just simply insurance too.

So what is Suh’s biggest expectation?

My belief in the market right now, because people are both understanding and trying to develop new applications and what some of the new technologies provide you is opportunity to actually grow the market. So my preference is more programmers, more data developers actually engaging, actually drives a bigger market opportunity for everybody.

The more the merrier. Real-time and context computing have Suh excited. The idea that we’re not only enabling machine-to-machine and connected core scenarios, but Big Data is enabling everyone. The democratization of data, not only for those Ph.Ds or data scientists.

“It’s really about liberation, being able to apply much more insights at the moment, at the right time and context place for the individual knowing the entity fully the second it happens.” Furrier summarizes the conversation with two simple words: behavioral and contextual. Behavior is the crowd, context is everything. Context in real-time is the future of Big Data.

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