 I think part of it comes down to when you think about people, oftentimes there's the ability to get lost in data, either in kind of the analysis of data or certain subsets of people that get lost through just the type of information you're potentially trying to extract from one dataset. So for me it's in part thinking about the bigger picture where we're going and to relate this back I guess to some extent AI consumes data and fundamentals we start to think about artificial intelligence. Data is to artificial intelligence as food is to people and so giving you kind of this additional layer of context by bringing together disparate datasets I think that you have a better capability to not leave people behind in that way and to kind of really get to the crux of what the data is saying as opposed to taking one individual dataset and saying that that is the de facto truth on this way you can kind of add to your contextual layers as you bring in additional sets of data along the way.