 My name is Johannes. I'm a research scientist at IBM's TJ Watson Institute. Most of my work relates to geospatial big data. So think about things like satellite or drone images, cell phone data, social media data, housing prices, census data. It's very hard to search across efficiently. Our group is developing a big data platform to effectively process this data and gain insights from it. This is a cloud-enabled service that allows you to develop insights with very little time and very little effort. Let's say you have an app that helps people plan vacations and you would like to, you know, make this app sort of data aware. So people choose their vacation target based on some information, like weather, restaurants. We allow you, you know, by combining your app with a cloud service to just very easily add this data. When it comes to using the platform as an analytics service, you tend to try to do forecasts or you tend to discover some sort of clusters, the sort of questions you ask with machine learning and AI systems. One example you might think about is disaster response. You're trying to predict what areas will be affected by a wildfire and this is an analytics problem that relates to where is the fire now, which is satellite, sensor data, possibly even data from phones, tweets, what people are reporting. But then, you know, to see how this is going to spread, you definitely need something about wind, not just the wind right now, but also a weather forecast for a certain amount of time. There are many advantages to the platform. Once the data, you know, is part of our system, it's all in the same projection. It all speaks the same language and you can cut through it, you know, in really very little time at high speed and get the information you want without having to worry about all these data preparation steps. Our vision is to give you a speed up that is basically from months to minutes, given the time it takes you to get insights and finish your projects. Whether you want to use this as an information service, as a discovery service or as an analytics platform, it's always the same API. An important aspect of the platform is its scalability. Both analytics, as well as simple queries, scale to almost arbitrary launch datasets. At the end of the day, this really allows you to worry less about the data and actually do your work, which is making discoveries, building applications and actually advancing your projects. In our experience, we find that since big data really permeates all parts of life, it brings value to almost all projects, to industries as diverse as insurance, finance, agriculture, but also to small startups and individual people.