 Bill Smarzo Studio B wanted to ask a few questions. Walk us through a day in the life, Bill Smarzo. What is it like for you to do your job? So I like to tell people I have the best job at EMCU. I get to spend all of my time talking to customers, right? Working with them and figuring out where and how to start their big data journey. So it's a, my average day is if I'm not actually traveling someplace in exotic locations like Des Moines, Iowa, and Omaha, Nebraska and Chicago and places like that. So if I'm not actually traveling and working with customers, I'm actually on the phone many times actually reviewing stuff, reviewing processes, trying to help them figure out where are the right business cases to go after? I like you called it a journey, a big data journey. And you know, you've talked about looking for business-led, business opportunity-led IT deployments. Tell us a little bit more about that. So the challenge that we've seen for the last, I would say the last 18 months is that for a lot of organizations, big data has been nothing but except technology. It's almost been a science experiment. And what's happened over the last four or five months is the business has gotten clued on to the fact that I have this wealth of data, both structured and unstructured formats. I have the ability to ingest this data in real time, and I have some massive analytic capabilities available. I can start teasing insights out of that data, insights about my customers, my products, my operations that really can help me drive better decisions and even create all new monetization opportunities. What has been some of the aha moments that your customers have when they finally grasp that and really look forward to the journey of themselves? So I think the area that surprises them most is that they're very heavily focused on trying to figure out how do I optimize my existing business processes, which by the way is a great place to start for a lot of organizations. But the aha comes when they start mining all that insights that come out of that process and realizing, oh my gosh, I have all these great insights that I can monetize in new ways through new products, new services, new user experiences, even package and insights and sell it to others. So that aha moment comes after they start of doing this optimization process and realizing that the byproduct is all these insights that's really valued by other parties. How can you kind of try to fast forward to that point? How can you, as you're educating people and businesses, how can you get them to really get to that moment sooner than they are in some cases? Well, it takes a corporate mindset on their part that really is about joining together and driving collaboration between the business side and the IT side. The groups that I've seen successful are the ones that bring both parties to bear and then we run a series of envisioning exercises with them to help sort of to imagine the realm of what's possible. Because they haven't really thought through, you know, I have all this unstructured data, consumer comments and notes from call centers and email dialogues and in those unstructured data sources are invaluable nuggets that can help them learn more about their customer's interests, passions, affiliations and associations that can impact the way they interact with customers. So the way that we do it is we can really drive collaboration between the business and IT. It's to run these envisioning exercises to really help people to sort of to envision the realm of what's possible. Are there any unique kind of case studies or just big ideas around these business opportunities that where it makes sense for big data that you maybe hasn't been implemented but has just been, you know, a really big idea in that realm. Well, I would say we're seeing case studies kind of popping up in two different areas. Number one, companies that are dealing with consumers. So retailers, banks, teleco companies, they're the ones who can get a lot of value out of their subscriber and customer behavioral analytics, right, understanding what kind of things their customers do, what kind of products take a light, how do they behave in certain situations? So that's a huge wealth of information, not only from a customer engagement perspective, but also from a developing and marketing products perspective. On the B2B side, the business to business side, we're seeing a lot of interest in predictive maintenance. So doing a project with an organization, they have wind turbines across the great state of Iowa and they're trying to figure out how do I optimize performance of those turbines and how do I do better predictive analytics? So again, business to business organizations are trying to figure out, I have all this censored telemetry data, how do I mine that to really help improve my maintenance predictability and drive better performance of all my operations? Fantastic. Mr. Smudger, thanks for stopping by at B2B. Yeah, thanks.