Implementing/Operationalizing Analytics At Scale & At Speed - Dr. Bonnie Holub

Speaker 0 00:00:10 Goal of data Speaker 1 00:00:11 Farmers' podcast is to accelerate digital transformation by bridging the gap between business outcomes and rapidly advancing technologies. And we aim to bridge this gap by focusing on data. I am Peggy PSI, top 50 women in tech influencer co author of the AI book and data governance expert. I'm an amazing entrepreneur and tech blogger on AI enthusiast. Speaker 2 00:00:43 Hi everyone. And welcome to another episode of data transformers with Peggy and rematch. I'm Peggy sigh, your data practitioner turned data podcast host. Speaker 0 00:00:58 So there are co-host of this podcast, the data transformers podcast, I'm the founder and managing partner of digital transformation pro Speaker 2 00:01:09 Thanks for mesh. And I'm so happy to have our guest speaker today. Um, Bonnie Halib, she's one of the leading data scientists at Terra data, and she's also one of the very few actually woman leaders in artificial intelligence and data scientists. So I'm so happy for Bonnie to be with us today and to really talk about the transformation transformative nature of data and artificial intelligence. It's really been a subject of, uh, many, um, organizations that are looking to transform and be good begin their data transformation journey. So welcome Bonnie. So pleased to have you here. Speaker 1 00:01:54 Oh, Peggy, it's a delight for me to be here. Thank you for inviting me. Speaker 2 00:01:59 Um, first Bonnie, I thought maybe, uh, you know, I did a very poor job of introducing you, but please share with everyone, um, you know, your exact title and role at Teradata, Speaker 1 00:02:13 Right? So I'm the practice lead for data science in the Americas. So I have a team of people from Chile, Canada, who all our principal, data scientists and senior data scientists. We, um, let me clear my throat. We work with a variety of clients, uh, uh, in all different kinds of areas, all the verticals. My summary is that I have a PhD in artificial intelligence, as you noted, and I've spent my career correlating disparate sets of big data for actionable results. Speaker 2 00:02:48 So can you give a little bit more detail in terms of, for each of the industries, um, that you work with? What type of business problems are you, sir? Are you solving with analytics? Speaker 1 00:03:00 Oh, there's just a really wide variety of them, you know, uh, when you go back and you, if you look at my LinkedIn page and you see my career, I started out as a Honeywell research scientist, and that was a really great job. It was a very academic job, but in industry where we were writing competitive research grants and getting funding and publishing papers. Um, and so in, when I was in that role, we were looking at things like combat information, fusion, uh, fusing together, all sorts of sensory reports that were coming into some kind of command center, so people could understand what was going on in the world. Um, in my role at Terra data, we have done a bunch of different things. We work heavily with financial services, uh, that's banks, it's also credit card companies. It's also insurance, it's all types of financial services. Speaker 1 00:03:51 And there we do things like fraud detection, um, real time at speed at scale. So if you can imagine helping one of the largest banks in the world predict what could be fraudulent loan applications as they're coming in real time, people are typing them on their computers and helping them predict twins. They can approve right away in which ones are going to take a little bit more level of approval or to at least be, um, evaluated before they make the loans that we do that kind of stuff. We also do things, uh, with healthcare, with healthcare and life sciences. So we have some of the largest healthcare companies in the planet among our clients and with them, we're helping them do everything from adjudicate claims quickly and easily to, uh, speed through processing of the financial parts of it, but also to help them maintain the highest level of health for their members who are covered with their health insurance plans. Speaker 1 00:04:52 So we also work with healthcare providers. We work with hospitals and professional associations of doctors and things like that, as well as other life science companies. Uh, when you think about pharmaceutical companies or also other kinds of healthcare manufacturing that have all of the highly regulated industry aspects of working with healthcare data and traceability of products through the production line, all the way through to sales and marketing, we also work extensively with retail. We do a bunch with manufacturing. Um, I think something like 17 out of the top telecommunications companies are two data clients, um, the largest banks in the planet or to your data clients. So we really work with people that have huge amounts of data that needs to be sifted through processed in real time, um, served at speed and at scale, and often in industries that are heavily regulated, they also require full auditability all the way through the pipeline. Uh, as a bank, you need to be able to know which criteria you were using for which loan applications at which time in case you're audited later. And you need to be able to get back to that state of the system at that moment to be able to trace it back. So I think we're really lucky in that we get to improve how businesses grow and how people live through the power of data. Every single day, we get to work on the most challenging problems on the planet. Speaker 3 00:06:29 That is a pretty, a wide breadth Bonnie. So I was just reading McKinsey report of AI global survey before our call and a couple of things. And I noticed. And so one is you really went through the different industries that you're working with. And one of the observations that they made after the global survey is that high-tech is the largest deployment of AI, right? And of course, but almost all industries are deploying AI based on your experience. Can you talk about which industries are leading in the deployment of artificial intelligence, which industries of trailers? Speaker 1 00:07:07 Right. Well, naturally trailing industries are heavily regulated industries like banking, financial services and like healthcare. And sorry, the reason those go hand in hand is that if you are heavily regulated industry with stringent documentation standards, auditability standards, master data management, data, government expectations, you are going to be reluctant to adopt new technologies until they're proven on a broader front, um, leading industries, as you point out include high tech or high tech manufacturers or some of the most, um, the thirstiest clients for our technologies and our capabilities. And that includes telecommunications. Um, and, uh, and then there's a bunch of industries that are kind of in, in the whole spectrum across it. Um, manufacturing, it depends kind of on what they're manufacturing. Um, uh, Oh, when you think about things like travel and transportation, that those are clearly challenged industries right now during the pandemic. And we have been working aggressively with our clients and the leading ones that we are seeing in those industries are the ones that are being aggressive about using their data to help improve passenger safety, improved spacing on ship, on flights, um, improve room turnovers, that hotels and things like that. Speaker 1 00:08:43 So it's a classic example where the best and the brightest are, are really being proactive in terms of retail. That's another interesting segment of the, that we haven't talked about yet. Uh, what we saw in March through September of this year was a complete change in how people interacted with retail, right? So some places had grocery delivery, uh, as kind of an option that you could get your groceries delivered, but all of a sudden, boom, in March, everybody wanted their groceries delivered. All, all of a sudden I had been using. Yeah, go ahead. Peggy. No, Speaker 2 00:09:25 To me, I think, um, there's just a big shift towards digital once the pandemic hit the United States. Speaker 1 00:09:34 Absolutely. And, um, and my colleague, uh, David King, and I did a marketing science Institute MSI interview with, um, doc doc, your barber Kahn, who wrote a book on retail revolution. She's really the leading experts. She's a Wharton school, uh, professor. And we talked about how we saw some of those things changed. So for instance, Walmart was leading grocery on, you know, online grocery delivery. And all of a sudden in April Instacart shot up and, uh, took over. And it was because Instacart could bring 300,000 people on board immediately to become shoppers in stores, um, and leaders like Walmart that already had some of that in place. They're continuing to do that. And other stores are not, uh, keeping up as well. But David has a whole theory, uh, that he's developed talking about buy online pickup at store. And the acronym is Beau pass, where you look at that whole transaction, there's a whole cycle of transactions that have to occur from the time somebody is looking at their cards till the time they fill it up, they might abandon it. There's, you know, less, um, uh, impetus to complete your transaction. Once you put things physically into a grocery store card, very rarely do you walk away and leave them. I mean, you know, the ice cream will melt, you know, but if you have a car that's done online grocery store, and then you go to checkout and you find out, okay, they'll deliver two weeks from Thursday, you're likely to abandon it. There's no cost to abandoned it. There are no public humiliation or anything. So anyhow, that's, those are things that we've seen change too. Speaker 2 00:11:23 Hmm. That's really interesting. And actually want to go back to your use case from the regulated industry and I've worked in financial services in the past. So I'm quite aware of really the benefits right. Of, um, you know, big data analytics to really help with prediction and fraud detection. And one of the things I've seen is, you know, the problems with data is the data quality, you know, the time it takes to wrangle the data, to normalize it Speaker 1 00:11:54 And get it to a point of where you could can do, um, you know, good analysis on, I mean, is that part of your role to be involved in the, you know, the engineering data engineering, part of preparing the data set, or does your role sort of, um, exclude that it can be, you know, we, um, when you think about trying to really be successful in business, you need data. Integrity is essential. So number one is data. Integrity is essential. Number two operationalization of everything you can is the goal. You want to get it operational. You don't want it to just be a nice little, um, idea that's in the lab, but that you didn't operationalize. Number three is you want to automate everything that you possibly can. So data integrity is absolutely essential and it's, well-known that 80% of data scientists at 85% of it is spent data wrangling, which is, you know, whether it's you call it data munching or data wrangling, it is figuring out how to get the data in the right format. Now we have a Legion of data engineers at Terra data who really specialize at that, but often we're brought in, in terms of strategically figuring out what we should do it, or do we need to, um, we want to maintain the integrity of the data and the statistical requirements of the data so that it will give us meaningful results. So we're certainly involved in that process, but it is essential Speaker 3 00:13:25 That that's right. So actually along those lines, Bonnie, if I could ask a question I'm fascinated by executives, like what are their day to day is like, right. So you touched upon the different things. Like what Peggy would asking is the data quality product you thing. So what is Vaughn is a week, even day to day probably is too much, but what's, what's a week like, like what are the kinds of things you're doing, uh, on a week at Teradata? Speaker 1 00:13:51 Well, it used to be that I get on an airplane and go to a one or two or three clients and visit with them onsite. And I still believe there's nothing that beats a face-to-face meeting for building relationships for really getting a sense of I've never passed up a factory tour or a plant tour, you know, just really seeing what people are doing in their business and understanding that I think is absolutely essential. Um, but now of course, right now I'm not doing that like many companies now, our company was essentially virtual. We always worked extensively with virtual meetings. And so that was no switch for us. We were in fact ahead of the curve in terms of that, it wasn't like we quick had to all learn how to use WebEx or zoom or any of those technologies. But, um, now I meet with clients and one of the things that's changed for me may have changed for you too, in the nature work. Speaker 1 00:14:51 And the pandemic is now I'm busier than ever. I don't know if that's the same for you, but it's, it's because you're home all the time and everybody knows you're home all the time. And so they, they book up your, your calendar with meetings. I'm not complaining. I'm thrilled to have a job during the pandemic. Like I say, I love the conversations I get to get in with, uh, with our customers, with our clients. And then I, um, spend, you know, a reasonable amount of time mentoring. I'm a player coach on our team. So I still have clients with whom I interact on a regular basis and, uh, have been selected to give up that part as I've gotten leadership responsibilities, just because I get so much energy out of it. And I learned so much. So my day is just packed wall to wall with meetings from Dawn, till dusk. Speaker 1 00:15:44 And I get to work with colleagues from all around the world, and I'm doing a number of different things on all of those. And some cases I'm bringing in key partners that I think would help us, uh, and grow our offering and provide greater value for our client. In some cases I'm demonstrating technologies that we have. In some cases I'm doing roadmaps with clients. They, they think they want to use their data assets in some way, but then I'm working with them to figure out what's the right order to use them in, what are the returns we're going to get? Are we going to do a, I like doing proof of value instead of just a proof of concept. So I like to, in what other people would call POC, I like to also have part of that be what value will this bring to the client? What will they get out of this? Uh, I have one client. I was meeting with the account team this morning where they use the 50 to one rule for every $1 they spend with us. We like to provide $50 worth of value, uh, so that they can really see the value of integrating the data and bringing it together. So these are aggressive kinds of goals, but it makes the problems much more interesting. Does that help? Is that enough detail for you? Speaker 2 00:17:02 That's a really fascinating, yeah, exactly. I mean, um, I mean, you certainly talked about, you know, the challenges of COVID and being locked down and I can certainly relate because I've been also been working, um, you know, extra long hours, but I certainly love to hear if you have any thoughts on, you know, some of the, some of the benefits maybe of being home or be more virtual and how that has maybe, um, positively, um, you know, impacted your career or work Speaker 1 00:17:37 Well last five jobs or so. And if you look back and look at my career, I had roles early on where I was 13 years with one organization, 15 with another organization, you know, really long and wide and deep, uh, in those industries, in those organizations. And I was in academia at the same time. So there was some overlap and the last few years I've had jobs. I had job changes just about every year for a few years in there. I've now been interior data for two years, but anyhow, it's interesting cause they, um, I had kids in college and I was recruitable quite frankly. Uh, but through all of those last, like five or six jobs, I've had the opportunity to work from home most of the time. And I significantly prefer that, uh, like most Americans, I like not sitting in traffic for a couple hours a day is a higher and better use of my time. Speaker 1 00:18:37 Um, having my commute be walking into my office. I like that very well. I also know that it's more challenging to create boundaries for yourself and boundaries around, uh, whether you have personal obligations, you need to fulfill taking a relative to the doctor or, you know, any of those, those things you just have to get on your calendar and block it out, let people know it's not negotiable because, uh, there is this incredible thirst for our time and attention on which is enthralling and fascinating. But I, I think that, um, many, many workers are going to like working at home. And I think that's, I, I think that's going to be a big change. Speaker 3 00:19:23 I think that is going to be a huge, huge change now is the pandemic. So, so Bonnie, I think now we want to get a little bit into your journey, professional journey. You started alluding to that already, right? I mean, uh, I looked at your LinkedIn profile, uh, by the way people can look at, uh, one is a, it's a very fascinating journey that you've had. So one of the things that really struck me when I looked at it, the breadth of experience that you had, you said in some companies, you are there for 13, 15 years kind of stuff, but how did you make the transition from one company to another? Is it an opportunity that came your way? Are you actively looked for it for a different kind of experience? Speaker 1 00:20:04 Well, I think it's been a mix of things. So, like I say, I started my career at Honeywell and it was while I was working there that they paid for my PhD master's and PhD in artificial intelligence. And so, uh, it was a very academic lab that I worked in day to day. So it was like, um, if I had been a graduate student in an academic laboratory, I would have learned a lot, but I learned it was like power tools that I had because I was in industry and I got to do a bunch of different things. And that's part of the reason I could be there so long as it was research, we were doing new things all the time. So it was never the same, never dull, never boring. Speaker 1 00:20:49 And I did have a chance during that time to teach, uh, and to become a tenured faculty member on a growing program in, uh, it was a graduate program in software that at the time I was, there was the largest graduate program software in the United States. There were larger programs that were computer science, computer engineering, but this was focused specifically on software and it was fun and exciting to be part of that. And that was a very entrepreneurial feeling. Uh, in the early two thousands, I had an opportunity to found, grow and grow a company. I sold it eventually, uh, called the millennium labs, which was a research think tank, not unlike what Honeywell labs had been before. And that was really fun too. I, I was thinking about your question. What do you do what's a day like in your life? And my sister-in-law asked me that early on in that process, she said, what do you do as the CEO of this company? Speaker 1 00:21:41 And I thought, well, it's a really small company when I get in there. And I'm the first one and I empty the dishwasher, you know, and I make a coffee and then I pay the bills and then I do cash flow forecasting. And then I read an academic paper and maybe critique, um, uh, something that's getting ready for publication. And, you know, you do everything as a small company entrepreneur, which is exciting and fun, but we did call it white, knuckle fun, you know, you're, it's like, you're on the rollercoaster you're hanging on and you're hoping you, you, that next contract comes in. And, uh, but you are, are living on that kind of a scale. Yeah. Speaker 4 00:22:17 So the point of all this is that Speaker 1 00:22:23 After I sold Advantium, I wanted to expand myself and grow into some new areas. So that's when I went to work with a, with a health insurance company. And it was a company that was growing at 40% per year. I mean, just huge growth, um, an exciting company that was growing out of a very mission driven organization and wanting to go grow responsibly and, um, very sensitively to the very diverse member base that this organization had and wanted to do so in an ethical perspective and also in a caring perspective, but doing it as frugally as possible, because of course it was not a huge company. Uh, and I learned a ton there and then I started getting recruited away. So then I got recruited away to, Speaker 4 00:23:17 To a bigger role Speaker 1 00:23:18 At a big four consulting company. And from there, I got recruited away to another role and another role in another role. So with each of those, I was always learning new things. And I, I love that, um, you know, one company I joined and my boss said your banking and financial services. And I said, okay. And from that day I was, you know, I, I got up to speed really fast. I worked with some incredibly bright colleagues who, uh, help me understand what their key issues were. And I, um, you know, did my homework, did my reading and met with clients and heard their concerns. And so that was it's, but it's really been an interesting blessing to have learned all these different things. And do I have worked in all these different industries? Speaker 2 00:24:05 That's so fascinating, Bonnie, and it, you know, your evolution, um, of your history is so fascinating. Um, one question I wanted to ask you was, um, in your, one of your titles, you call yourself a storyteller. And after hearing you actually explain your, you know, your data, your career journey, I could, you know, I could definitely see that, see why you call yourself that, but I would just want to, um, ask you to maybe explain or clarify, um, storytelling. And I think that's so critical, especially in the data field to really be able to explain and to relate the data. But I just wanted to hear your, your answer in your own words. Speaker 1 00:24:49 Did you see my, I did a post a couple of weeks about what to be an award-winning storyteller, and you probably can't hear that this is my trophy storytelling. I mean, I'm actually an award-winning storyteller. Uh, the short version of that is when I was in high school, I competed on the speech team in the category called storytelling, where you didn't have a defined script. You had to speak extemporaneously, you had read a story. So you had an idea of who the characters were and where the story was going. What the moral of story was, if there was one, but then it was up to you to tell it in a dramatic way so that people would, um, understand the point of view of the characters, see the conflict, feel the rev revolution, sorry, feel the resolution when it comes about. And, um, and in a way where they listen both with their brain, to the facts that are going on, but also with their empathetic part of their being so that you, um, can really put yourself in someone else's shoes. Speaker 1 00:25:56 And at the time I was so apologetic about being a storyteller. It was, you know, I had colleagues on the team who were delivering great speeches or being dramatic monologues from, you know, major literary works of place. And I was telling stories, which to me just sort of felt like, you know, I got, I felt like I got this because I didn't have the discipline to do other stuff. I didn't know what it was. All I had was a really insightful coach. She said, this is the category you have to compete in. It's a skill you have and you have to hone it and get it, make it better and time. And again, in my life, I have gotten the moral of the story, Ben Ellis story. So as a young professor, I went to the seminar on delivering meaningful lectures. And the whole point of the eight hour day was tell a story. Speaker 1 00:26:47 And then when I went to a sales seminar later in life for some professional training, they said, tell a story. So in retrospect, I count my lucky stars that they haven't aligned. And then I got that training very early on in my life. Um, I certainly have used it every single day in my life and I enjoy it. Right. It's more interesting to me, if there's a story to it, it's not fantasy cold facts and business, the stories of value, how are you improving the lives of the people that, that business touches? How are you improving the health of the patients at a hospital? How are you, uh, improving the financial stability of families all across America with better mortgages and more stable loans, except by creating value through your banking and financial services client, you know, it's, it's that kind of thing. You have to see what it means to people and connect with that. So thanks for asking about it. That's one of my favorite topics. Speaker 3 00:27:47 Great, Bonnie actually, um, I think people who are good storytellers, uh, have been more successful. I mean, that's what the research shows. So along that if I could just interrupt for a second, so go ahead, Speaker 1 00:28:00 Um, to people who, uh, have learned to speak English, a British school system, like a lot of people who were trained in India and other parts of Southeast Asia where they might've had British school system telling tales is not a good phrase, right. Telling stories is a metaphor. It's a, um, sorry, it's a synonym for lying. Exactly. Yeah. They'll say don't you tell tales. Speaker 3 00:28:28 Yeah, no, no. Intel, yeah. Story telling is different from telling stories. Speaker 1 00:28:32 Yeah. And so I always like to try and make that distinction too, especially when I think there's an audience that has that interesting different backgrounds. So thank you for helping me do that. Speaker 3 00:28:42 Yeah. Yeah, exactly. So storytelling is an art and then yeah. Telling stories has a different meaning to it. So one of the things that Peggy, um, uh, reference at the beginning is that there are fewer female executives in the technology industry, and I think it's inspiring to see female executives and Peggy, I think, are hopefully going to ask this question. So what has been your journey as a female leader? Uh, I mean, you're definitely an inspiration to a lot of people. Uh, was it, uh, with obstacles and did you have to overcome, or the mentors? Can you talk a little bit about that? Speaker 1 00:29:19 Well, um, sure. So my experience has really kind of interesting because when I went to college, I went to a college that up until a year before I got there had been an all men's college. And frankly, I went there out of curiosity. I want to know what they were teaching. Those boys know it was a college that had a reputation for, uh, generating successful leaders in industry and government and the professions. So I knew it was a good school. I was just so curious what it was like. And so at an early age I had to, and there were definitely faculty members who didn't think it was a good idea. There were definitely students who had chosen to go to an all male school that didn't want these female students coming in. But, uh, anyhow, it's, it's what was going on. It wasn't, I don't say that it was ever felt unsafe or anything like that, but it was, it was just an environment where I just had to just I'm I'm there, you know? Speaker 1 00:30:19 Yeah. And then I majored in computer science, right? So the ride many classes where there was no other women in the class. And then I went to work in the military industrial complex, and there were a lot of women in that work either. But, you know, I had years already of experience of, you know, I, I enjoy working with men. I liked being on teams with men. I had a sense of all that. And, and I was also relatively young. So when I get started, I thought a lot of times I was asked to speak at something because I was a woman. They wanted to show some diversity, but I thought, okay, I'm here because of that. But after 30 seconds, it's all up to me to keep the audience and to say something meaningful. And so I, I did, and I talked to young women all the time now who say, Oh, I'm in this room. Speaker 1 00:31:13 And there's nobody that looks like me. And I say, congratulations, you've got a super power. No one will forget you. And everybody will know who you are and what you say. So use your super power wisely. Right. And I don't see that as a, a challenge at all. I am thrilled that women are making meaningful strides forward and getting more leadership roles and things like that. And, uh, and I have many friends who are in various industries who are also female, who are strong leaders and, you know, strong leaders hold other people up. So the most successful women that I've known, just like the most successful men are the ones that are always trying to pick out new talent or make sure somebody gets an extra chance at something or another try or, or get the, um, get the credit for the good work that they're doing, uh, and really provides an environment where other people can shine. And then, you know, we're all stronger because of that. Right. Speaker 2 00:32:20 That's right. Yeah. That's, that's really great advice. And I love how, you know, we just being really in a supportive environment, um, can really encourage that. Um, so Bonnie, one question I had for you as well was like, who do you see as your influencers? Like who, who do you look to? And especially, Speaker 1 00:32:40 You know, you know, throughout your career or even today, um, who do you see as, as someone that, you know, you're trying to learn from, or, um, you know, or what do you read at night? I'm just curious as to like, what keeps you fresh and motivated? Right. Well, you asked me about mentors too. Um, interestingly enough, at this all-male college, there were two departments that were headed by women. And I ended up double majoring in both of them. One of them was English and I majored in English just because I loved reading. I loved being part of it, but I didn't see that as a career for me. And I majored in computer science because I loved it. I loved writing programs. I love the technology. And I did see that as having a rear, a real career focus. Uh, and I think those were probably the only two departments headed by women at that time at that school. Speaker 1 00:33:34 And, uh, the woman who led the computer science department turned into a long lifelong friend, dr. Bernice Foles is a member of the, uh, Minnesota tech association, uh, lifetime honorees for her work, uh, growing educational programs in computers and software engineering in the state of Minnesota and continues to be a friend of mine has been a mentor to my children. Uh, and I certainly give her credit for that. I had mentioned my speech coach, poly Ray. Kaliski another great person who put me in the right place to learn things at the right time. And I've had a slug of fabulous male and female mentors in industry all along. And the reason I maybe had them was because I wasn't shy. And I would see people that I thought highly of and would just figure out ways to work with them and get in their sphere of influence so that I could learn, watch them at their best. Right. You want to see the very best people, but do whatever they're doing and you want to emulate it and practice it and learn from them. So I've been lucky that way, but I'm feeling like I'm a little bit off topic. Do you want to get me back on? That's perfect. Speaker 3 00:34:45 Okay, perfect. So this is the last question, um, for you. It it's been just fascinating. I can, uh, I'm just, uh, very fixated on the discussion here. I'm sitting where we are, lots of investments are going into artificial intelligence and other technologies. So what are the trends that you see going forward, uh, and data science and AI, and in this area that you're operating, Speaker 1 00:35:10 Right. Well, you know, a lot of the investment that's going into like startups, my posts are because people have kind of a good idea and they think they can scale it up and they think they can do things with it. The same pressure is there full, larger stale companies, boards of directors are demanding machine learning, be implemented places. And that, uh, they're realizing the power of analytics. Uh, Oh, you asked about who I read. Well, I certainly read Michael Lewis, anything he writes, I read Hans Rosling, uh, I read, um, you know, lots of technical stuff. I am recently reading a story on data, a book on data storytelling by Brent dykes. Um, and then, uh, I read history. I read business books. I read, um, fiction. I love fiction. I usually have two or three books going at any one time. Um, but to me, I notice things like, I think it was 2018 or 17 during the super bowl. They had the official analytics provider for the NFL. Speaker 2 00:36:18 Correct. There you go. Yeah. The CEO's in the Speaker 1 00:36:23 Box suites around the stadium or seeing the official, uh, analytics provider and say that, okay, it's going to be a huge year because the people that sit on boards of directors are going to say, what are you doing about analytics and AR how has your digital journey of your company? The problem is that everybody has these good little ideas and people have trouble getting it implemented and operationalizing it, weaving it into the fabric where it can really work. So we have our biggest and best retail clients retrain 10,000 plus, uh, predictive models every single night they have, uh, they don't just segment their customers. They hyper segment and they have their 100,000 groups of most valuable buyers. So for me, the challenge is how do you operationalize analytics at scale and at speed and not do it in little silos? You know, do a little extract, train a little program, throw your analytical over the wall to it and expect them to implement it. Speaker 1 00:37:25 It's I think it's absolutely important to be working in an ecosystem where you can get to the data training analytics, have them trained on the scale that you need flip them into production, because they've been built in things like R and Python and things like Jupiter notebooks in our studio, but also where you can do it in a way that will have master data management, uh, full data governance, all those other kinds of things that are absolutely required. So to me, it's really the industrialization of AI and the industrialization of machine learning and other advanced analytics. That is where the meaningful change is going to come from. And we see it among the very best and the best of breed clients that we get to work with. Speaker 2 00:38:14 And hopefully, and hopefully at next year's super bowl, we'll see artificial powered by artificial intelligence and who knows it's right around the corner. I agree with me. So with that, uh, so thank you much for your time. Speaker 3 00:38:36 Uh, I know it's very precious, but thank you for giving us an audience at time. So thank you for listening to today's episode. If you liked what you heard today and would like to hear more, please subscribe to our podcast on your favorite player like iTunes and Spotify. And please do rate our podcast. Also, please go to our website, www.data transformers, podcast.com for more episodes, blogs, and information on our speakers. Thank you. Speaker 0 00:39:17 <inaudible>.