 Hello and welcome to My Career in Data, a podcast where we discuss with industry leaders and experts how they have built their careers. I'm your host Shannon Kemp, and today we're talking to Mark Hirschberg, a fractional CTO, CPO, and author. With a robust catalog of courses offered on demand and industry-leading live online sessions throughout the year, the Dataversity Training Center is your launch pad for career success. Browse the complete catalog at training.dataversity.net and use code DBTOX for 20% off your purchase. Hello and welcome. My name is Shannon Kemp, and I'm the Chief Digital Officer at Dataversity, and this is My Career in Data, a Dataversity Talks podcast dedicated to learning from those who have careers in data management to understand how they got there and to be talking with people who help make those careers a little bit easier. To keep up to date in the latest in data management education, go to Dataversity.net forward slash subscribe. Today we're joined by Mark Hirschberg, a fractional CTO, CPO for several companies, and author of the recently published book, The Career Toolkit. And normally this is where a podcast host would read a short bio of the guest, but in this podcast, your bio is what we're here to talk about. Mark, hello and welcome. Hi, thanks for having me on the show today. It's my pleasure to be here. Oh, I'm so grateful that you joined. It's been a while. We've known each other for quite a while, but haven't interacted for what did you say, a decade? It's been probably close to a decade since we last were connected. Yeah, well, I'm so grateful that you're here today. And I'm so excited to, in our little pre-show, we talked about what you've been up to. And I'm excited to share this with everybody because it's some really, really cool stuff. So let's get into it. So, OK, so first, I have to ask, you're the fractional CTO and CPO for several companies. So tell me what companies you work for. How does that work? How do you represent many companies? It's a few different companies. And these companies all have one of a handful of needs. They say we have some technical work, software engineering or technical product. We don't necessarily have the need for someone full time in this role. So for some companies, they say we've got an engineering team. We might even have like a director, but we need some more senior leadership. And that might be at the strategy level or working with key partners. We don't need you 40 hours a week. So this basically lets them really get the best ROI for their money because they can hire me for the limited number of hours. I'm not doing the day-to-day project management. Oh, what's the status of this ticket? Let's move it around. I just focus on things where you need so of my level, similar to the fractional CFOs that have been around for a while. Now, that's one type of engagement. Sometimes they say we just lost our CTO or CPO, Chief Technology Officer, Product Officer. Can you stand in? We're going to hire someone in three months. We just want someone keeping an eye on things for a little bit. No big decisions. Just make sure we don't go off the rails. Occasionally companies come to me and say, we have a CTO or CPO, but there's about 1.2 times the amount of work they can handle. So they're going to focus on the important stuff. And you, we're going to give you the maybe lower ROI or lower priority products. We can't ignore them. And we need someone with enough seniority to be on top of them. But it's really not where our full-time person should focus. So in this case, I'm acting as a part-time deputy, just covering some projects. And then occasionally they'll bring me in. This is more short-term engagements. All of what I described is usually longer term, a few months to even years. Sometimes, especially recently, because of the trend towards AI, people bring me in just for some consultant, come in for a month, give us some help with strategy. I've gotten a lot of that lately because of my background in machine learning and AI. Boards and executives are saying, come in, talk to us, give us some help. Where should we look? And that's usually more of a one-off, a fixed number of hours or a project for about a month or so. Oh, that's very interesting. And I'm sure that keeps you busy and keeps what you do a bit diverse in the industries that you work for. Do you find it varies from company to company dramatically? Or is it pretty much the same type of work for each role? It has varied a lot. In some cases, we are building greenfield technology. In some cases, I've got legacy technology that we're trying to advance. I had one company, they had me come in as a fractional CISO because my background is actually in cryptography. I've done a lot of cybersecurity companies as well as AI and ML and enterprise software. So there I said, just focus on our security issues and then lately some of these AI projects and that's in very different companies and they're looking in very different ways. So there is lots of breadth across industries and the scope of the work that I'm doing. It's fun in that there's a lot of variety. It can be challenging in that I'm doing lots of context switching and even here's someone named Chris. Oh, wait, Chris is a product manager at this company but no, I'm at this other company. Chris here is someone in sales. I just have to always make that switch which can be a little taxing. Yeah, well, that's very organized, very detail centered. Yes, and the calendars, this is the biggest challenge of the job because a lot of companies for security reasons don't allow the sharing of calendars. Oh, uh-huh. I often, when I have a meeting scheduled at a particular client, I have to duplicate it on my own master calendar or I'm not gonna see it because when you have one job, you're in your calendar in your email every day. When you've got multiple ones, you're not always checking. That's probably the biggest challenge but when you learn to do that, it can be a lot of fun just to deal with all the different clients and challenges. It sounds like fun. I love mixing it up which I get to do a lot here at the university which is fabulous. So now you're also the author of a new book, The Career Toolkit. So tell me about the book and what inspired you to write this? 20 some years ago, we created a class at MIT referred to colloquially as the career success accelerator. We recognized our students are pretty smart. They can do the math and they were going to be okay. They would get jobs but our students were effectively getting the biggest cubicle and not the corner office. We are producing the leaders of tomorrow especially since if you think back 20 years we knew technology and data were going to be so important and our students engineering students not just at MIT but elsewhere we've got the skills for the upcoming jobs but we're not getting those leadership roles. What was going wrong? We realized they could do the math but the other skills they were lacking leadership, communication, teamwork, negotiating, networking we've heard all of these skills we've been told they're important but no one actually sits down and teaches them to us. So we wanted to address that and we created this class I've now been teaching there for over 20 years and for all this time I've said you know our students they get in the class but students are very good at forgetting everything as soon as they walk out of the class as soon as that last day the finals are over everything disappears. Well, that's not helpful. I also said you know it's not just our students let's get this to other schools for various reasons we didn't have the capacity at MIT to really expand it. And so I was just gonna write up some notes I thought this will be some takeaway the class by the way it's not lecture-based it's interactive so the students aren't even taking lots of notes but let me write up some notes for the students and maybe we can share this with other schools as well. So my intention was to write 10, 20 pages of notes a takeaway for the students. Well, those 20 pages quickly became 40, became 80 and once you have the hundred I said I don't think I'm writing notes I think I have a book here. And so unintentionally I wrote the career toolkit. Oh, I love that. And you know we talk so much about that in this podcast because you're right. I mean so many technical personnel go into it without those soft skills without those networking skills. And that has been one of the big themes in this podcast is that networking and finding mentors and being and continuing to learn to as you say succeed in that career and get beyond the cubicle. Let me give an example. Suppose you are 25 years old and you learn to negotiate. You have a job offer for $70,000 but instead of simply saying I'm going to take it you say wait I know how to negotiate and you try to negotiate with your future boss to get just $1,000 more. We can all imagine doing that. If you do nothing else but that one five minute negotiation and you get the $1,000 more now you sit in that job for the next 40 years with five minutes of effort. You read a single book on negotiating or took an online class, however you learned it with just a little bit of work you just earned $1,000 more for the next 40 years. You got yourself $40,000 with a few hours of reading and five minutes of negotiating. But of course you're not gonna stay in that job the rest of your career. You will have raises and promotions and other jobs and you'll negotiate and you will get more. If you get just a little bit better at negotiating we're not talking about you can solve Middle East peace just got a little bit better. You can add tens of thousands or even hundreds of thousands of dollars to your lifetime income. Now I'm using negotiation income because we can do the math but the real secret is if we get just a little bit better at communicating, at leading, at networking it's not that someone says here's $1,000 more but opportunities will come or you will be first in line and you will advance your career. You will have more success whether that is in terms of dollars earned or in other metrics of success that matter to you. So getting just a little bit better at any of these skills or even all of them can have this compounding effect on your career and really accelerate you. Oh, that's, I love that. And I'm so grateful that you put this together and have put this in a book for people to read the career toolkit. You also took it, I'm gonna add a little teaser here which I'll come back to but the little teaser you took it a bit further and created an app, Brain Bump. The Brain Bump and to help retain some of that information but let me come back to that because first I wanna talk about how you felt your success and where you came started from. So when you were very young, was this the dream, Mark? Was it when you were in elementary school just a little kid, say five years old and like, I'm gonna grow up to be a fractional CTO and CPL and an author of the career toolkit. What was the dream? The dream was maybe a little more adjacent. At five, I wanted to be a stockbroker. Oh, wow. At nine, I wanted to be a physicist and I did get one of my degrees from MIT is in physics but I decided not to go into the field. In ninth grade, I first got really introduced to computers. I was doing a little, maybe a middle school on my own or in my elementary school, we had logo but it was my first formal computer class in ninth grade and that got me into computers. I said, I want to do software. So I knew back then I wanted to get into the field but I had very specific views, said, software is great. You get to build things. You don't have to deal with people and stupid people issues and management and wearing suits. Oh, that sounded horrible. I never wanna take a job where I have to dress up. Ironically now, I work in tech. I work for a lot of startups. I don't, especially post pandemic who does but I interestingly like dressing up. I wear French cuff shirts most days. I have a huge coupling collection. So my views have changed. In fact, the people issues got very interesting. Early in my career, I started as a software engineer and I realized the people issues are harder than the engineering issues because engineering issues, okay, are we scaling or compute time or are we scaling more memory and we can go this way or that way and there's rules and constraints when we think engineering, here's the formulas, what do we do? But for people, for every rule about people, you can pretty much find an exception. It's so challenging. I thought I like hard problems and boy, this is really hard. So my original intention, I was going to technology but I wanted to be individual contributor. I don't wanna deal with people, give me a problem, I'll solve with the computer. And now I actually find the people issues, the strategic business issues, I really enjoyed that part of it along with the technology. Oh, that's an incredible journey. So how did you discover that? So you went to major in technology, so then how did you get into, what was the next step? You said you were a software developer. So where was the journey from there? How did you, that led you into writing a book on careers and how to network and how to engage with people? I was getting tripped up a little because I came out of MIT and I was a little cocky. I'm a smart guy, I've got some degrees, I can do this. And I could do the math, but some of the other things I couldn't do as well. I was putting my foot in my mouth, I was not conveying the information the right way to the right people. Didn't always understand the business context in which my work existed. These little things were tripping me up. I started reading books on project management and realized on the one hand, all the books were the same. You have the constraints, you have cost time scope. Now I'm just talking about different ways to balance those. But when we get to the people side of it, I noticed there were all sorts of different advice and it was a lot less clear. And that's what opened my eyes and said, there are some other things here I don't yet know. They seem to be important. I seem to be screwing up because I don't know them. So that's what opened the door and got me to think differently about these skills. I love that you were curious about something that you were struggling with. And I love that. So tell me more. So where was the next job for you and how did you start building that career using those skills? I knew at the company I was at, I could stay there, they liked me. I have a good job as an individual contributor, but I wasn't really going to grow. I might have grown more technically getting more advanced projects, but I wouldn't really flex my muscles other ways. So intentionally chapter one of the book is about creating a career plan. And I said, well, if I want to get somewhere, there are some intermediary steps I need to get to including developing myself, not just technically but in these other areas, this job isn't going to give it to me because our compensation is not just what's on the check we get. Our compensation is our learning and growth and happiness and the environment we're in. And so I recognize I wasn't getting the compensation I wanted, not monetarily, but in this development. So I looked for jobs, I was very fortunate. This was right before the dot-com crash. So a job for Plentiful. And I found a job and convinced them, you should put me in charge of the engineering team. Now that might sound crazy for a kid who at the time was 26. I just turned 26. But if you think back to the dot-com era, the start-ups were being run by 22-year-olds. There's the famous saying in the land of the blind, the one-eyed man is king. I didn't know much, but I knew more than some of these kids right out of school. So I did have value to add. And admittedly I did learn a bit on the job. I did bring value, I wasn't totally lost, but there was also plenty of learning in that first job. Nice, very nice. And then where did you go from there? From there, I spoke to some of my mentors and we talked about, I've been at that job for about two years. I felt with time to move on. We had sold the company and I didn't like the direction we were going in. So it's time to move on. And my mentors had said, you should consult because with consulting, you're going to get more variety. You can do more targeted short-term projects. I haven't been a consultant the whole time. I've gone back and forth. Today I'm back to being fractional CTO, which is a type of consulting and think of it that way. But I've also gotten back and forth full time. Back then though, I was lucky I found a job at Harvard Business School. So here's the interesting thing. I saw this job, they were looking for someone for $15 an hour. I could not work back then for $15 an hour. But the job seemed interesting because the compensation I would get wasn't just whatever I can convince them to pay me, but also I would learn from these professors. I knew nothing about finance. I thought working with some finance professors at HBS, that had some value. So I met with them and convinced them. I said, look, tell me about your project. They told me, I said, look, you can't hire someone part-time $15 an hour to do what you're trying to do. You need a professional like me, maybe even more than one of me, but you're gonna need more money because we cost more than that and convinced them. So they went out, they got more funding. They hired me, they hired another guy and we spent a year building out a simulation tool that's now used to teach finance at HBS, also used for certain types of research. But the best part about it wasn't simply the money. I sat three feet from a professor in his office for a year and it began the first two weeks. I told them, I said, I don't know anything about econ or finance. Said, no problem, they gave me a bunch of books. I'd read the books at night. We'd have tutorials during the day. After two weeks, I had the basics and then of course we continued as we went or students would come in for office hours. I'd be the fly on the wall. That's funny because the professors would often tell me after it's like, yeah, here's stuff I'm not gonna say to the students. And so I joked that you have a thousand people a year who pay Harvard Business School to learn finance. Right. HBS to pay me to learn finance. I love that story. More and more companies are considering investing in data literacy education, but still have questions about its value, purpose and how to get the ball rolling. Introducing the newest monthly webinar series from Dataversity, Elevating Enterprise Data Literacy where we discuss the landscape of data literacy and answer your burning questions. Learn more about this new series and register for free at dataversity.net. Okay, so let me back it up a little bit. First of all, you had mentors. Yes. So when did you start reaching out and acquiring mentors? You're giving me too much credit because early in my career, I was not that wise where I said, hey, can you be my mentor? But these were people I had unintentionally built relationships with. I encourage people now I'm more intentional with that. But all of us do have relationships with people and there are people you admire and respect. And very importantly, we often think of a mentor as more senior than us. Don't look chronologically, a mentor is anyone who knows more about you in a particular field. Classically, we think of the stereotype of the older person and then the 22 year old with the latest technology and social media. I had my cousin's kids when my books came out. I said, can you help me with social media? I knew what social media was. Hey, I'm a tech guy. I can figure out the mechanics, but I didn't think well enough, like how should I really use Instagram? But guess what? The 22 year old daughter of my cousin, she knew more than I did. And I could learn from her in that. Now I taught her things career wise. She really enjoyed the book. So a mentor is anyone who knows more than you about a particular area and can offer you advice. And all of us have these people, whether you formally said, will you be my mentor or not? You already have them. You can create formal mental relationships if you like, but you can get advice from lots of people. Well, I love that you asked for advice, that you had this curiosity and you were thinking about a change and you solicited advice to help process that decision. So many try and do it on their own. I think you're so alone in decision-making, but you're not, you don't have to be. And getting help is a really big thing. And then I love the story of, I love that you got paid to learn. And that you, but you saw that, but bigger than that, you saw an opportunity for a job that you thought you'd be really good at, but it didn't quite fit. And then you went and negotiated a way for it to fit and benefit you and them at the same time. And I think that is a really, really nice story. Quite a few of my jobs are jobs that did not exist. They were not saying, this is who we need to hire. Yeah. I invented the job. Now, in that case, I took a small job and expand it to something that worked for me, but there were other cases, whether it's clients who weren't trying to hire me, but I heard they had a problem and went and explored and said, let's do this. And so I'd say probably at least a third of my jobs, I used to know the ratio I haven't looked at lately, but about a third of my jobs are ones I made up. It was not a job post I responded to, it was not someone saying, here's the need. They talked them into it. That's amazing. I love that boldness and confidence. And did it always work? Not always. There are certain people like, hey, I can help you. And they go, that's nice. All of us can do this because a job is basically solving a problem. Boy, I wish I had an app. Oh, I know how to write code for an app. I can do that for you. Boy, I wish I had more sales. Oh, well, I'm a sales guy. I can find you customers and convince them by your product. That's what we do. We are solving specific problems in our job. So when you hear at a company, maybe even your own company, someone says, this is a problem. If you can solve that, you can create a job for yourself. Now you have to convince them that the cost of you doing that is less than the benefit that they get from you doing that. There's some sales going on in there. There's some convincing. It's not a simple five-minute conversation, but that's really something all of us can do. When you hear someone with a problem that you can solve, there is an opportunity for a job. It's very true. It's very true. So was it, did you just remain then in consulting through from there on out, in and out, like you say? I went back and forth. I consulted for a few years and while I got the variety and good exposure, I did miss being committed to a single company. And so I came down to New York, committed to a company. That company blew all its money very quickly. We raised a lot of money. We went through the money very quickly. The CEO spent money like a drunken sailor. So I went back to consulting for a bit and then went back and forth throughout my career. There was a period of probably a good 10 years from about 2009 or 10 through about 2020, 20 or 21, I think 2020, where I was pretty much a full-time CTO, CPO at a single company with very limited consulting in between jobs. What an amazing career mark. I mean, really, that's just, that's really exciting. And again, I love the boldness of it. It's just such a great story and great examples of how you can take control of your career path. And so now with all that in mind, what has been your biggest lesson so far in your career that you take away and that you use every day to push you forward? It really is the importance of these soft skills. Now, I gave the example of how it can help you in terms of compensation, but let me give you a different example. We're gonna do some math. I do this with my students. I even put in the book. I know this audience can handle the math. Imagine if you will a rectangle that's four by 10 and you have to increase one of the sides by two units. You want to maximize the area. So which side do you increase? The short side or the long side? And if you need a moment to pause, you can pause a podcast, think about. But now that you're back, the answer of course is we increase the short side. We go from four to six, 60 units. What does it have to do with careers? Well, let's think conceptually what's happening. There's two extra units on the short side amplify that long side. If you put the two units on the long side, they're only amplifying the short side. All of us have short sides and long sides, more than two. For most of us, most people listening to this podcast, some of our long sides are technical skills, we're very good, we're better than the average person, maybe even better than many of our peers. And that's great and we want that skill. There are accountants whose long side is slightly different, sales people long side are slightly different. And we do have to continue to work on that long side, especially in technology. We know if we're not paying attention, if we're not developing that skill, we're out of date. We're using old technologies, no one will hire us. So do work on that long side and that's why we have professional development. All the great things at data diversity, the classes, the conferences we go to, the blogs, we need to keep up with that. But on a per unit ROI, working on the short side gives us a bare return, it increases the area which is our capability. So let's take a canonical example we know in tech. We all know, we may even be the person who is so good technically that really long side but when they speak, when they present to the company, it's nearly incoherent. This might be because they just don't present well. It might be because they can speak well but it's so much technical jargon and all the non-tech people just go, I don't get it and they tune you out and they're on their phones during your very important talk. And it's because you have this great long side but your ability to communicate is not so good. If we can make you a slightly better communicator whether that is just being able to give a speech for our people or tuning down the technical jargon and learning how to express it in other ways or for other people, it might be your teamwork or your leadership. If we make that just a little bit stronger, we're taking that long side you have and making you so much more effective the overall area of this rectangle. And so I learned early on because if you think about what we did in school, especially technical degrees, we got more and more narrow than this area and just solve the problem, get the answer as quick as possible. But in the real world, it's not just getting the answer, it's getting buy-in, it's communicating the answer, it's negotiating because some people don't like the best answer but maybe there's a compromise in there. So developing all these other skills will make us so much more effective. Don't ignore your long side but work on your short sides too. I love the how you present that is very understandable especially to, it's just very understandable especially as I have a more scientific background from college and not that I've retained a lot of that information but we will talk about that later. So Mark, so you know, you've talked a lot about your background in science and the various sciences and the soft skills but what's your current definition of data? So I'm assuming as you've used a lot of data throughout your career, you've processed a lot of data even especially as a CTO and CPO but what is your definition of it and how do you work with it currently today? Great question. I certainly have worked with a lot of data. I've run data science teams, machine learning and I've dealt with volumes of data especially in ad tech. I've also dealt with complexity of data. My work on the dark web, we're getting information, we're tracking terrorists and criminals so you have a lot of unstructured information across multiple languages looking for signals. So I've dealt with a lot of different types of data and data analysis. Data to me is really just a raw set of facts for observations, that's data at core and then we need to take that data and use it to create information or inference or guidance for what we wanna do in the future and data when you and I first met over a decade ago there was an article around the time that said data is the new oil. Data is driving the economy and this is when big data, that was the exciting term and certainly it is if you think about where we've come in the last 10 years and even where we're going, the amount of data not just ad tech, the amount of medical data we're getting, the amount of data from all the IoT devices from the fact that a bus 10 years ago, I live in New York City, the bus was just driving along. Now of course the bus is showing where it is every minute and you can track it but they can also do optimizations. So we have this just ever growing mountain of data and now as we're recording this in 2023, what's the big thing? AI, well AI, it's a version of machine learning. It's just how much is pre-trained as we see with generative, chat, GPT pre-trained AI versus doing real-time machine learning as we get data feeds, but it's all the same concept. And so data is really driving a lot of the technological innovations and a lot of the tools and services that support modern life. So data really is the oil of our modern economy. It's so, so true. So then do you see the importance of data management and the number of jobs working with data increasing or decreasing over the next 10 years even? And why? 100% increasing. Now people are saying, wait a second, our jobs are at risk and AI is going to take them and there will be some of that. But we know historically technology destroys jobs but creates new ones. There may be a lag, one of the big risks is if those new jobs don't show up before the old ones get taken away, we can have some unemployment and I have lots of articles on that. I do think overall we will see an increase in data jobs not just because it will create new ones but again, just the volume of data. Those buses I described 10 years ago, no one was tracking that data. And now maybe New York City buses isn't a full-time job but though I'm guessing you probably get enough data for the New York subways and buses, they have a team of data scientists but your small town, not a full-time job but you add up 10 of those towns and some county says where you attract the bus data, there's a new job that didn't exist and someone tracking wheat harvest all across the globe, literally a camera looking at the height of the wheat each day and saying, what are we projecting? There's data coming in and there's someone who has to think about capturing it, analyzing it, interpreting it. So data jobs will continue to grow because the amount of data we have will continue to grow. Such cool examples of data. I really, for every industry, there's no industry that doesn't work with data. Absolutely. So what advice would you give then to people looking to get into a career in data management who are maybe just discovering data and the possible uses of data? Unway had a great Venn diagram. This also goes back 10, maybe 15 years about what it takes to be a data scientist. Now, this applies not just to data scientists but all of us who work with data. I said, there's three parts to it. First, you have to know the tools. If you can't work the tools, you're not really useful. You also have to understand the math because we know if you don't understand math, lies, damn lies and statistics, you can start to go off in the wrong direction. But even if you understand the math and the tools, you also have to have domain knowledge. You have to understand how this model, this data, this answer can help or hurt a business. So you need to have those three pieces. Too many people focus, they get that very long side in maybe the first, I know the tools well, or yeah, I know some math, but they might be short on understanding the industry or you get someone who, oh, I know the industry. Oh, I took a data science class, I did two weeks, I get how this works, but they don't really understand the depth of it. So we want to make sure we are well-rounded. We're not way too short on one of those sides. Now, I would add another piece to all of this. Data really underlies so much of what we do in business, whether it's guiding our decisions or the stories we tell, data provides information, data provides direction, data misused, going back to those lies, damn lies and statistics, especially certainly in the US, but even abroad, math education isn't where it should be. There are people, if I didn't have ethical guides, I could BS them and do some math and do effectively numerology and convince them the world is flat or whatever I want to do with the data. And so we, as people who work with data, we have an ethical responsibility to use data properly, to understand how to use these tools and the data and interpret it and then to communicate it honestly and effectively to help guide our clients, our companies, our customers because if we don't, we could take that same data and we can create not information but misinformation. We can not guide but misdirect. And so it's very important that we be ethical in what we do. It may even be time for us as an industry to have some type of ethical standard. Doctors have the Hippocratic oath. We may need something, now it's more complicated. When you're a doctor, it's very simple. First, you know harm. There's a patient here, don't harm the patient. With us, it's not, there's easy, good and bad because data usually says something is changing and that's good for something and bad for something else. It's gonna be a lot more complicated but we definitely do need to take ethics into account in our work. It's very, very sure. And it is merging as a topic more and more which I'm very grateful to see lots of conversation going around data ethics. What is and what isn't ethical? And especially, you know, as things like generative AI come to fruition and come forward, you know so many discussions around ethics. Yeah. Oh, so, you know, Mark, okay. So you've had this amazing career, so bold, so smart. Just really very impressive and the career toolkit. Now, I added in that teaser at the beginning earlier about how you took the career toolkit a step further with the BrainBomb. So tell me a little bit about this app. I got a brief demo of it in advance. I've already downloaded it, it's free y'all. So, you know, don't hesitate to reach out and download it. So tell me a little bit about what inspired the app that you can use, upload your book into even. The free BrainBomb app available on Android and iPhone stores was designed to take content from books, blogs, podcasts and other sources and make it more accessible. I mentioned earlier, my students, they would learn in the class and they forget all and when they needed it, it wasn't there. Yeah. When you read a book like my book or other business books or even self-help the problem is where you read information isn't where you need information. I have a chapter on networking. You're going to read that sitting at home. You're going to need that at your next Dataversity Conference where you wanna meet all your colleagues in the industry. You're gonna say, oh, what were those tips I read two months ago? What if we could give you that information when and where you needed it? So the BrainBomb app, it's like a cross between a book summary app, a flash card app and a daily affirmation app. So we take content from books, blogs, podcasts, classes and talks, put into the app in tip cards. So it's like flash cards, although it's not, you have to do the question answers just there for you. Now one way you can use it is just in time as you're about to go to your next Dataversity Conference right before you walk into the room whereas you're in the elevator headed down, open up the app, all the tips are tagged by topic like hashtags. So for that, you'd pull up the topic, networking and there are the tips and just flip through some of those cards and go, all right, there's a tip. Yep, I remember you said that, okay, that's good. And now you're ready to go. You're getting the information just in time when and where you need it so you're more effective. Now the other way you can use it is you might say there's foundational knowledge that I'm trying to retain. Another example for my book, there's a chapter on management. Maybe you're a first time manager. Now you can't say to someone in a conversation, wait, hold on, I gotta pull up the app and look up what I'm supposed to say to you. You just need to remember that. Now no one wants to use an app every day. We're all busy people. So you can set up to get a daily reminder, let's say 9 a.m. each day as you start your job. It just gives you a simple push notification with one of the tips, line or two, few sentences. And you just look and go, oh right, yep, that was a good point. Swipe it away. Two seconds a day, you don't even need to open the app but you're getting that repeated exposure, space repetition, we all remember that from school, that's going to help you retain it. And so all of this is in the app, it's completely free. Now currently as we're recording this in the summer of 2023, the 1.4 version of the app is out, the 2.0 version coming out at the end of the summer not only has all these features plus more but if we don't yet have the book or podcast or source that you want, you'll be able to add your own tips whether you enter them in directly or you can download your Kindle highlights from some of the things you've read and just import those tips and use it the same way. So this tool helps you retain what you've learned whether it's that foundational daily reminder or pull it up just in time because I know we can't remember this but you've got all the things you've learned right in your pocket when and where you need them. Oh, I just love it so much. I would even go so far as to say it's like having a mentor in your pocket. You know, there's so many times in so many situations where I've been in a conversation and like, oh, what was it that I was supposed to remember and what was it that I was really impressed by in this moment in this book and that would be so handy to have to be able to pull that out and go, oh, yes. Here's the very important thing. I had that same problem because I had read things. There was something somewhere in the second half of the book about this thing. I can't remember the details. So now, for example, I have in my book, I use the, in one chapter, I use the parable of the blind man and the elephant. If you don't know that, you can look it up online or you can read it in the book. And if you're thinking, wait, there is something, something said is about elephants. No problem, you open the app, type in the word elephant because we have a full search function. There you go. There is the key takeaway of that parable right there in your pocket. So it's all there for fast recall. Ah, lovely. Well, Mark, this has been such an amazing conversation and really impressive again. And I would be remiss if I didn't ask, how do people find your book and the app? You mentioned that already is available in the Apple and the Android. But how do people find your book and how do people find you if they wanna solicit any of your services? I mean, I give you two websites. First, the careertoolkitbook.com. There you can see where to buy the book, Amazon Elsewhere. There's also a weekly article that I put out so you can see my writings on other things coming up. You can get in touch with me, follow me on social media. There's a page of free resources. If you're interested in having me speak at your organization or you need a fractional CTO or CPO or advice on AI, reach out and I am happy to work with you. The second website. So the first, the careertoolkitbook.com. The second website, brainbumpapp.com. Now you can just probably look at BrainBump in the store directly. If you go to brainbumpapp.com we have links to take you to the stores. There's also a 90 second explainer video that's gonna walk you through how the app works. And remember, BrainBump is completely free. So the careertoolkitbook.com and brainbumpapp.com. Ah, so great. And we'll post those on the website with the podcast and make sure and get those from you. So for anybody out there we can look it up and with the podcast. Well, Mark, this has been a really great conversation again and thank you so much for taking the time to chat with us today. Thanks for having me. I appreciate your time and now the audience. Ah, and to all of our listeners out there if you'd like to keep up to date on the latest podcast and in the latest in data management education you may go to dataversity.net forward slash subscribe. Until next time and stay curious. Thank you for listening to Dataversity Talks, a podcast brought to you by Dataversity. 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