Lauren Brousell: Hi. This is Lauren Brousell. I'm a staff writer for "CIO Magazine." We're here today at day one of the CIO 100 Symposium. Let's hear what some of the CIOs had to say about big data and analytics, and the ways that they're getting better insights and better competitive advantage. Man 1: One example for getting better insights on data analytics is we used to have to have all the data in PowerPoint. Now we have direct access to 10 billion data points for the new SMAP mission. Interactive, real time give great insight, which can save a lot of time for our [inaudible 0:29] . Woman 1: The example that I like to give is we have the Affordable Care Act, which is a quasi government agency that needs to share information with our healthcare policy folks. That's our Medicaid people. The way the process works is an individual goes in and shops for health insurance. Before they can get private health insurance they have to see if they qualify for Medicaid. That information needs to be exchanged between those two agencies. Now with this infrastructure I have that in place. It's helping process healthcare applications much quicker and more efficiently. Man 2: I would say pricing. We're involved in helping manufacturers and retailers determine what's the appropriate price for a product at the shelf. Big data is obviously very helpful for us to get the right product on the shelf everyday. [pause] Man 3: The challenges of getting to good data quality in analytics is that you really don't need good data quality in analytics. It's a culture shift. You don't dig for gold everywhere. You figure out where the gold nuggets are, and that's where you dig. Rapid exploration of the data before you spend a lot of money is the way forward, we think. Woman 2: The challenges that I face is the bureaucracies and the deep cultures. I have 17 different state agencies that were individual, think of them as individual businesses, until 2007. Then this office of information technology was created. It's a relatively new organization trying to interact with deeply rooted bureaucracies and cultures. Man 4: Largest challenge would be well intentioned expert employees who are experts in different fields that know they need to use big data, but they haven't had the training yet to be able to aggregate the big data into the picture that's helpful to them. They can wind up immersing themselves in too much data and not enough information.