Ulf Zetterberg: It’s almost like a knowledge management system because if these self-service systems are built the correct way, an intelligent user can leverage this as a knowledge platform and perhaps do advance queries. It becomes almost like a dialogue. There’s a big debate in the legal industry about the automated lawyer or the IT lawyer and
Sramana Mitra: This is actually a good segue to my final question. Where do you point entrepreneurs to look for opportunities for building new companies? I think we’ve already started that discussion. If you take the base layer of unstructured data and then on top of that, you look at the different application areas. You
Sramana Mitra: You say it’s broader than that. The unstructured data problem in the enterprise is a broader problem, but I believe it’s going to get solved in pieces just like the contract problem will be solved at the contract lifecycle management level. Then there are other types of unstructured data in the enterprise. There
Sramana Mitra: What does an enterprise account look like for you? Ulf Zetterberg: Enterprise accounts are very distributed and fragmented. It could have two or three fairly old legacy data sources. It could be that the applications have been there for five to ten years. The usability and transparency is very poor. It’s a big
Everyone in Big Data is anticipating the Internet of Things trend. Don discusses it as well, along with other issues. Sramana Mitra: Don, let’s start with introducing our audience to you as well as Infobright. Don DeLoach: I’m the President and CEO of Infobright. Infobright is a company that offers a purpose-built platform for storing
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
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
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