Sramana Mitra: You’re saying that the structured data integration problem at scale is still an open problem? I’m looking for problems that are unsolved out there, not problems that you’ve solved already.
Bob Renner: I think scale is an unsolved problem at this point. A very difficult problem that you have to solve elegantly is cross-domain master data management (MDM). I think you’ve got a few products and solutions and implementation within a given domain and a less complex domain had been adequately handled, but I think cross-domain master data management is a problem that continues to be very use-case specific, and generally, there have not been a lot of solutions.
Bob Renner: In one example and use case, we married our sales data with Twitter feeds so that we can access the API’s. We pull the data in, normalize and correlate it, and we created a dashboard that allowed our clients to look at sentiment. We were able to dimension that along with the sales data. We product a very different, simultaneous view of geography, volume of sales, and demographics of who they’re selling to and then generalize sentiment about how people are talking about the data from social media standpoint. The interesting part of that is it uses some forms of natural language processing and parsing to take free-form data and turn it into structured data from the Twitter feeds and marry it up to other structured data.
Sramana Mitra: Let’s do a couple more use cases from different industries.
Bob Renner: Let’s go all the way over to distribution. Two of the largest distributors in the US of a variety of industrial supplies as well as paper products leverage Liaison’s technology to pull in information about the products that they then package and sell, normalize that, and synchronize that data to their ERP systems. In one case, one of those two very large distributors has a fairly common ERP model. The other one, a direct competitor, has a geographically distributed ERP model. Both of these companies use Liaison’s cloud-based integration and data management platform as the authoritative data source for all of their products that they pull in and also a variety of attributes related to those products. >>>
Entrepreneurs in the field of data integration would like to read this interview to get a sense of the state of the union, and identify open opportunities in the field.
Sramana Mitra: Bob, tell us about Liaison Technologies and yourself.
Bob Renner: I’ll tell you a little bit about myself first and then I’ll dive into Liaison. My background is in the technology space. I call myself a technologist by trade. I joined Liaison Technologies almost 15 years ago as a Chief Technology Officer. Then, I moved up from CTO to CEO after being with the company for a couple of years.
Sramana Mitra: What is your corporate incubation strategy? How do you drive innovation in your company?
Paul Zolfaghari: I think our innovation strategy comes down across a couple of different vectors. We’re very interested in seeing what trends are in the industry. What are the leading visionaries talking about and thinking about? We certainly listen to our deep and very impressive customer base. Honestly, if you get the chance to talk to a Netflix, American Express, or Citibank, you’re bringing together the collective wisdom of trillions of dollars of GDP. That’s a good sample set for us to get from. >>>
Sramana Mitra: What are the white spaces right now?
Paul Zolfaghari: In terms of what I think people are looking for in the market that nobody is really working on, I think you’re going to see a more pronounced interaction between gesture and gesture-based interfaces and the ability to interact with analytics and analytics benchmark. I think it’s not that far down the road before you’re going to see gesture-based technologies in the way people are interacting with their proprietary environment. Is that a white space? I don’t know. Maybe somebody’s working on it.
Paul Zolfaghari: What we have been doing as a company is ensuring that the MicroStrategy analytics and visualization layer can be that primary interface, but that where the data resides for us is becoming less and less relevant because we’re ensuring that we can attach and interact with that data wherever it is. What’s happened from a trend standpoint is that the introduction of Hadoop and Hadoop-like vendors has dramatically lowered the cost of storage and storage of data. >>>
Sramana Mitra: That’s the modus operandi from the point of view of your large customers. Do you have customers who are independent software vendors who are also developing on top of your analytics platform, and are providing the business logic for maybe a particular vertical and then selling? >>>