Sramana Mitra: When you say you want to monetize the data that you have, what does that mean? I can understand what kind of data your clients have. Are you saying that your clients are already collecting a certain level of data on your system that you have not yet built applications on top of?
Mikko Jarva: What our solutions traditionally do is they support the process of billing and charging of data. Billing and charging of data has been done on the data generated by networks and channels that end users utilize. Traditionally, that data is only utilized for billing and charging of telco services. There are more ways of using the data for intelligent recommendations and further monetization of services. The first step of monetization of telco customer data is to provide better recommendation of the telco services to get the end users to use the services more. This can be done through Big Data and intelligence.
Of course, the parallel step is to utilize that data for monetization of third-party services. As I mentioned earlier, telcos have a holistic view of their customers and end users. They know their customer’s location at any given time. They know what kind of applications they are utilizing. They know who they are communicating with. At the same time, telcos are highly regulated. They need to be able to take into account their end user’s privacy. With intelligence, we provide better recommendation for the end users.
Sramana Mitra: When you look at this general space, and I’m asking you to lift yourself to a 30,000 foot level, point out some open problems that your customers would like to see solved from a Big Data standpoint.
Mikko Jarva: Firstly, there was a lot of hype around Big Data. With that hype, there was a lot of focus on the technology of Big Data itself and not so much on the application and use cases. The first challenge we see is how do we get beyond the hype. How do we go beyond the technology and into the real world applications? How do we take the technologies inside and put that into use?
Second challenge that we’ve seen is Big Data is very real. Any digitally connected enterprise is flooded with data, and that flood is increasing. Everybody knows the three V’s of Big Data – volume, variety, and velocity. All those three are increasing. The volume of data is increasing. The variety of the data is also increasing. There is a data management problem as well.