Vitria CEO JoMei Chang on Big Data and Operational Intelligence

On this episode of Big Data TV, host David Feinleib speaks with JoMei Chang, CEO of Vitria. They discuss Operational Intelligence, Big Data, transactions, and real-time. Watch now!

Dave: Hi, I’m Dave Feinleib with another episode of Big Data TV, brought to you by Today we’re in Sunnyvale, California at the headquarters of Vitria, and we’ll be talking with JoMei Chang about the company and a great space in Big Data called operational intelligence.

I’m Dave Feinleib, I’m the host of Big Data TV, brought to you by I’m here with JoMei Chang who’s the CEO of Vitria. Today we’ll be talking about Vitria and operational intelligence. Great to have you on the show.

JoMei: Thank you. Great to be here.

Dave: Great. Maybe we can start out talking a little bit about what Vitria does, and a little bit about the operational intelligence category.

JoMei: Sure. We focus on innovation, so Vitria is really about technology innovation and how to use technology innovation to solve big business problems. So Vitria was founded in 1994 and the problem that we focused on at that time was IT integration. We pioneered two categories of products, enterprise application integration and business process management. Both categories are substantial market segments for enterprise software. Five years ago we saw Big Data on the rise, so we started focusing on a prominent space in Big Data we call operational intelligence. Today Vitria is the operational intelligence company.

Dave: That’s great. What does operational intelligence mean?

JoMei: Operational intelligence is a vast growing market sector. Loosely speaking, it is about performing analytics over company data. But today most of the companies in that space perform analytics over machine data.
Dave: Right.

JoMei: At Vitria we take it one step further. We perform continuous real-time analytics over company data, but not only machine data. It is over Big Data, streaming events, business processes. In addition, based on the continuous real-time analytics we enable continuous insight and enable the company to take immediate action.
Dave: So machine data is things like log files generated by servers, network devices, things like that.

JoMei: That’s right.

Dave: Obviously there’s lots and lots of data there. What are the other kinds of data a company might be working with?

JoMei: Analyzing machine data is like doing a forensic analysis first, but the company has much other data. The business data, the transaction data, and what’s relevant to their business processes and business transactions usually goes across multiple systems. So it’s really relevant to how well the business is doing, not just how well the IT system is doing. In some sense, what we consider are the three pillars of operational intelligence are visibility, insight, action. A company has to be able to see all their data. The streaming events, the business data, the transactions, how well everyone’s doing, and then be able to monitor that and present the significant event through a live dashboard. That’s what we call real-time visibility.

Dave: Interesting. Then who looks at the dashboard? Is that a chief marketing officer, is that a general manager?

JoMei: I think it’s all of the above. I think it’s the end user, and the end user can be a business user or can be an IT analyst, but not just only looking at the dashboard. That’s only a portion of the total impression, a company also has to be able to base on those and have analyzing and reading understanding of what all this data they see really means. You have to be able to correlate that information from different sources, be able to match the pattern and provide insight. That’s why we say data is different than insight. Insight will enable a company to make intelligent decisions. Then of course, last but not least, a company based on continuous insight is able to take action through preset businessprocesses. It’s really sort of a wide spectrum of activity, but provided by one single unified platform.

Dave: OK, great. Do companies install your software, do they get it in the cloud? How do they consume the product?

JoMei: They get it from both. We provide it through the cloud, or provide it throughon premise fashion. That depends on what our customer is comfortable with, because some of our customers, large enterprise customers, like to play with the cloud first, but they are at this stage-

Dave: But use the software, yeah. So, talking about specific customers, you don’t have to mention names, what are some examples of the kinds of customers that would use your product?

JoMei: For example, let’s take Telco. We have a customer that’s an international, very large, mobile provider. They get hundreds of millions of eventsa day of network device data. However, when this network event device problem happens, they don’t know how that affects their most important valuable customers. They may be a high-paying customer, so that’s a problem. So what we do with OI is to correlate the billions of network event data against the customers’ data in a continuous real-time fashion such that whenever there’s a problem occurring, they can pinpoint and identify which high value customer is being impacted. They can then, based on that, make intelligent decisions on what action to correct. It depends on the importance of the customer or the financial impact. Similarly, a similar example goes to financial services customers. Banks can monitor hundreds of financial events a day, but they need to read it, monitor that, compare against their performance goals, to make sure they meet SLA at the end of the day for the customers. More importantly these days, they comply to the regulatory compliance. All of those require the continuous real-time imagery.

Dave: So hopefully in theory we could avoid another financial crash, or might even have my calls not get dropped when I’m driving around Mountain View.

JoMei: Yes, and in theory you can also use that to many other industries, and we will have customers in the utility industry use that for customer satisfaction, we have a customer in the cyber security space to use that to detect the cyber threat. You can also use this to identify opportunities, not just threats.

Dave: Yeah. So a lot of the talk in Big Data of late has been around the shift from batch to real-time. We’ve seen a bunch of funding announcements about companies that are commercializing things like Hadoop. Where do you see some of the up and coming trends and technologies in the Big Data space? Are you seeing things? You talk about real-time, but talk a little more about what real-time actually means for a customer or for a consumer.
JoMei: Sure. I think, first of all, a lot of the work in the Big Data space is about storing and access of Big Data, such as Hadoop making the storing and access easier and easier, which is very important. But on the other hand, you only address half of the problem. That is the problem we call Big Data at rest. A big segment of the problem is what we call Big Data in motion. That is, the data stream that’s happening right now and how do you access it or how do you analyze it, and how do you continuously analyze it. That’s what we call Big Data in motion. That problem today is compared to the number of companies and innovations that have been focusing on Big Data at rest.

Dave: So a lot more companies in the infrastructure are in storage.

JoMei: That’s right. They’re focusing on storage, but they’re not focusing on Big Data in motion. What we also look at to perform real-time analytics is good, but you also need to be continuous real-time, and not only on Big Data at rest, but also Big Data in motion. Let me give you for example of continuous real-time versus just real-time. If you want to know about stock information, I give you the choice. Would you rather look at the stock ticker-tape, the stock information that keeps on coming at you, or every time you want to know the price you hit the keyboard, you see the price, the next time you hit the keyboard, you see the price? By the time you see the information, the information has already outdated.

Dave: Right, got it.

JoMei: Your choice. We choose to solve the continuous real-time, and we choose to solve both Big Data in motion and Big Data at rest.

Dave: OK, that makes sense.

JoMei: But in addition, not only just real-time analytics, but also continuous insight and immediate action.
Dave: OK. A lot of aspects of that Big Data application level, let’s say. OK, great. Looking ahead to the next couple of years, this was called by the New York Times the crossover year for Big Data. Obviously you saw Big Data five years ago. What do you think the next five years hold in this area?

JoMei: I think the Big Data problem is only going to get bigger. People and companies are hopefully starting to address what they consider as the real problem, that is how to unleash the value out of Big Data, not just trying to survive in the Big Data world. They’re trying to unleash the value of the Big Data. What does that mean? For many years, Big Data in motion understanding and the process what’s going on right now, and the philosophy of the data, is the philosophy of business change increase. That means that there’s more pressing for real-time, but not only for real-time, the continuous real-time. But to me, the most important aspect, the third point, is to empower the end user, because end users are the ones who have the domain knowledge, they understand the business value. You have to enable and empower the end user, such that they can continuously in a real-time fashion to explore and experiment with Big Data, and get the insight the experiment more, such that they can truly turn Big Data into the comparative web. That is the old saying, turn your data into a comparative advantage, everyone knows how to say that. But having more data, that doesn’t mean having more insight. These days, having more data means you’re more lost in the insight. It’s really about the three points I mentioned. Big Data in motion, continuous real-time, and empowered end user.
Dave: Great. So, one last question for you on this topic. You’re a CEO. What advice do you have for other CEOs who are reading a lot about Big Data, but are perhaps trying to think about how to or what to do with Big Data in their organizations. What advice do you have for them from an organizational perspective, but also from a technology or an implementation perspective?

JoMei: I think Big Data is here to stay, and everyone needs to jump in and to start leveraging the data that they have in their organization. What I always say is, this is the time for business change occurring, records re-occurring, and business changes a lot of times are driven by fear and bad greed. Whoever jumps in first, embrace Big Data, be able to leverage the value and unleash the value of Big Data. They are the ones who are going to make most of the money, and then the rest if they get left behind, because of the fear, they either want to catch up or they get left behind, then it’s over.

Dave: Yeah, great.

JoMei: So, that’s it?

Dave: That’s it. Fantastic, thanks so much for being on the show. We may spend a minute or two looking around at the office with you, but it’s really great having you on the show.

JoMei: Excellent, thank you very much.

Dave: Thank you, OK. So it’s always nice to find out a little more about the personal side of some of our founders and CEOs. We’re here with JoMei in front of a fountain out front of Vitria. Tell us a little bit about how this fountain came about.

JoMei: We moved into this building when Vitria was still a start-up and hasn’t decided to go to IPO, so we had a very limited budget in terms of how to decorate the building. But I always wanted a fountain in the building, because that represents the continuous water flow, continuous source innovation, and is very soothing. I saw with the designer that the building had a beautiful fountain, and it was a 250 something dollar price. The designer told me, JoMei, you cannot afford this on your budget, no way. I said, I agree, it’s too expensive, but it doesn’t stop me from wanting a beautiful fountain. So I went to the San Francisco Home and Garden Show and I saw a very small copper fountain. I looked at that and I said, that’s beautiful. I asked the artist, can you make me a larger scale for the fountain? He looked at me to say, sure, why not? So, I ordered the fountain.

Dave: That’s great.

JoMei: And here you are, we paid a fraction of the price for the fountain in the affordable range of a start-up, and the fountain was delivered a week before our IPO, and arrived here with the water flow, with the innovation. Here’s the fountain.

Dave: That’s such a great story, and it’s a beautiful fountain, by the way.

JoMei: It represents to me that anything is possible, and you just have to give it a try.
Dave: So we’re here today with JoMei, CEO of Vitria. Give us that quote one more time, because I think it’s such a great quote for entrepreneurs and CEOs.

JoMei: I think that one, everything is possible. The other one is, people who do not believe it can be done should not be in the way of people who are doing it. That’s my motto in life.

Dave: That’s so great. Well thanks again, it’s been a real pleasure.

JoMei: Thank you.

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