Sramana Mitra: If you were to present the industry layers of infrastructure that are going into making that transition from analyzing samples to analyzing actual data, what does that landscape look like? Todd Goldman: There is the raw data warehouse, which today is evolving to be the Hadoop layer. I don’t think the legacy appliances
Sramana Mitra: Are there any other verticals? Todd Goldman: Telecommunications is another one. This is a never-ending topic. When I started my career in HP years ago in network management, I sold to the telecom market, and they were trying to solve the problem of churn.
Sramana Mitra: I would like to take three of your customers where this is happening. Let’s talk through three use cases and customer scenarios. Todd Goldman: There are two major scenarios that we are seeing of how people are using Hadoop. One is that over time, companies have bought traditional data warehouse appliances. They have
Todd Goldman is the vice president and general manager for enterprise data integration at Informatica, a company that provides data integration software and services based on big data analytics. Todd holds a BSEE in engineering from Northwestern University and an MBA in Business from Northwestern University – Kellogg School of Management, having worked for IBM,
Sramana Mitra: How mature is your learning model at this point? Matti Aksela: In the sense that the extract was working on predictive analytics solutions for 10 years prior to being acquired. The first release of the social links product was in 2006 or 2007.
Sramana Mitra: I fully understand the information of who called whom, for example, is also proprietary information for the carrier and the carrier can do whatever they want with it. That is not exactly social network behavior. It is more about information about transactions happening within the customer base. What does that tell you? What
Sramana Mitra: Are real customers using this product? Matti Aksela: Yes, there are customers using this. One of them is from Bangladesh, and they announced they are going into production right now, for example.
Sramana Mitra: Let’s double click down into that field. I would like to hear three use cases of customers, where you use these kinds of predictive analytics to solve problems or achieve meaningful business goals. Matti Aksela: We can start with one of the most traditional use cases in the mobile operator space – finding