Danny Ma_mixdown.mp3

Danny: [00:00:00] I think in general, just we should really be out there to help others instead of trying to help ourselves in a way. Like I know of a few larger names who the social media presence is, their business, essentially. And I know that's really important. Like everyone has to make money, feed their families, buy all the things that they need in life and all that aspirational sort of things. But in a sense, like for me, like I don't know if this is this might be similar for you as well.

Harpreet: [00:00:38] What's up, everybody? Welcome to the Artists of Data Science Podcast, the only self development podcast for data scientists you're going to learn from and be inspired by the people, ideas and conversations that will encourage creativity and innovation in yourself so that you can do the same for others. I also host Open Office Hours. You can register to attend by going to Bitly.com/adsoh forward slash a. Ds0h. I look forward to seeing you all there. Let's ride this beat out into another awesome episode and don't forget to subscribe to the show and leave a five star review. Our guest today is a recovering data scientist who is passionate about guiding businesses and individuals on their data and machine learning journeys. He's internationally known for his warm presence, humble nature, dope memes, affection for SQL and for staying up all hours of the day and night to bring you the guidance you need in your journey. As a testimony to his unwavering dedication to helping others succeed. He has built a loyal community of over 5000 aspiring data professionals and is working towards his vision of creating a scalable virtual [00:02:00] data apprenticeship program to further the knowledge and experience required to be successful in this field. So please help me in welcoming our guest today, the chief data mentor at Data with Danny, the people's data scientist himself. Danny Ma. Danny, thanks so much for taking time out of your schedule to come on to the show today. Man, I appreciate having you here.

Danny: [00:02:22] Thank you so much for having me here. Harpreet It's amazing. It's an honor to finally catch up with you live and for the audience of Data Science podcast as well.

Harpreet: [00:02:32] I mean, a long time coming. I know this pleasure and honor is all mine. It's been a long time coming and I was trying to get you on the show last year, but you're busy, busy cooking up something amazing with this serious SQL stuff. Man, I've been able to take a peek at what you've been doing with all the work there. And all the work with Data with Danny has been awesome to see. We'll definitely get into all of that, but let's learn a little bit more about, you know, we're talking preshow a little bit about this, but talk to us a bit about where you grew up and what it was like there.

Danny: [00:03:02] I'm from Sydney, Australia and I've been here pretty much all my life. My family moved over from Hong Kong to Sydney when I was two years old and I have been here for 28 plus years, so it's really been awesome. I think I'm a first generation Chinese Australian and having that sort of culture and mindset leads to very specific experiences and I would say like very shared experiences across some of my friends as well. So it's been very interesting. I think everyone's life is really interesting and for me, looking back on what I've happened to achieve throughout my life, I think it's almost like watching a movie when you think back on what you've done personally, I'm sure there's much more ahead for me as well as for you as well.

Harpreet: [00:03:47] And yeah, you know, just just trying to do something big now. That's really what it comes down to. But, you know, I mean, you just celebrate a birthday last week, so a happy belated birthday on that. And I mean, I did I didn't realize you're so [00:04:00] young, you know, compared to me, like, I'm almost 40. You just turned 30. So you've definitely got a long and prosperous career ahead of you with all the stuff you're doing, man. But Sydney is awesome and I've absolutely loved that place. So my wife and I, when we got married, we waited a year to take our honeymoon and we decided to go to Australia and we went to Australia in end of June. So it was like wintertime, but it was fine weather for us and we did a road trip from Sydney to Melbourne all along the coast, but we spent like about a week in Sydney and I absolutely loved it there. So I had one of my students was a math for a while and he had moved to Australia, Sydney for a while and he worked at this place called Palmer and Company or Palmer and CO. It's like a cocktail bar, really, really swanky place showed us around a little bit. And the hotel my wife and I ended up staying at was in a nice hotel, but it was in Kings Cross and I didn't realize how wild and nutty it gets out there. Man, that's cool. Sydney is such a cool place, man. What's it like? What's life in Sydney been like for you? Like, have you come to like North America? Have you done like a compare and contrast that what's what's different? What's the same?

Danny: [00:05:11] Yeah. So when I was doing my undergrad, I had the chance to go on an exchange semester. So I actually went to the University of Alberta for one semester. It was really, really, really cool, really cold there as well and went for like the fall semester. So towards the end it was getting really nice and chilly, which was great because it was the first time I saw snow in my life. So that was really amazing. But yeah, I visited, I did the whole like. Exchange student thing where you kind of try and hit as many cities around the area as possible. So I went to all down the West Coast in the US first. So we joined like some sort of tour on a bus and we just kind of bused around all of those different cities like San Diego, San Francisco, L.A., I think we went down to Vegas as well, which was really cool. I think at the time I was not of age, [00:06:00] so we were like trying to find ways of getting around it because in Australia I think the legal drinking age is 18 and in, in the US I think it's 21. 21.

Harpreet: [00:06:10] Yeah, yeah. That's cool man. Yeah. I mean I currently live in, in Winnipeg which is the province over from Alberta, so it's like not too far from where you're staying, but. Talk to us, I guess, you know, we talked about where you grew up, what it was like there, but like what kind of kid were you during high school and what did you think your future would look like?

Danny: [00:06:30] That's a great question. My childhood was very, I would say, typical, like a Chinese Australian who was forced by their parents to do a lot of studying. So I had like a. I would say almost like Tiger parents, but I had a Tiger mum and she would try and get me to do everything that my cousins were doing and they did a lot of tutoring. They ended up going to the top high school in I think Sydney and maybe in Australia. So I went through that whole experience of doing all that and but my dad on the other hand was the one who was forcing me to do a lot of variety of things. So my father's, I would say, is like my life's idol. He's sort of like the the stereotypical. Man of the house, but he's very, very kind. Has a lot of time for his children. I was his only child, so he had a lot of time for me. And I spent all of my time with him. Literally, if I wasn't going to school, he was taking me to play some sports, do swimming, play some musical instruments. He was always driving me from place to place, and he's got this mentality of always wanting to learn. So coming from Hong Kong, when he came to Australia, he didn't he didn't have a job. Essentially. They left everything to come to a new country to try and come out with relatives. So for him, it was he didn't speak English properly. He didn't have [00:08:00] any of the skills that were transferable. And he ended up like he was a librarian for a point in time in Australia. Which was ridiculous and pretty cool, though. Yeah. Like I think he's he's very inspiring in that sense where he's just gone off and done a lot of different things that no one really would expect him to do.

Danny: [00:08:21] And in primary school, just finding it hard to find a job. So he ended up taking like a I don't know if you guys have it in Canada or the US, but there's like people with there with a stick and like a super supervisor of a crossing, like a children supervisor. We call them like Lollipop Lollipop man because he looks like he's holding like a lollipop. He was doing that for many, many years when I was in school, and he loved it. He thought of himself as like the guardian of the children as they were crossing the street sort of thing. And I actually went to my final year of primary school. A grade school was with with the local school, which was nearby. And I changed schools. And when I moved in, everyone knew me as like the lollipop man's son. And it was like I was like famous for a little while. So it was really awesome. And I think I don't know how it would have went these days or if it was in high school. It might have been a little bit different. But I think back then it was just amazing and I had just a really great mentor and father figure and my mom was really, really smart, so she was like teaching me high school math by the time I was in primary school from very, very young age. So I kind of had that mathematical training, but I wouldn't say that I'm gifted in math at all. Like, I just kind of I'm good at solving problems and learning new things. And that's about that's about it. A lot of people think of us like skills.

Harpreet: [00:09:47] They have good skills to have, though.

Danny: [00:09:49] Like people always think of us as really, really great and like theoretical math or pure math or anything like that. But I don't know. I've. I just enjoy solving [00:10:00] problems and the math just happens to be part of what I had to learn to solve a wide array of problems. So, yeah, no, I just love learning stuff. Just like my dad. He's like, he's almost 17 now. I'm still learning. So he is like. Recently he was doing a bachelor's of dementia or mental health at a university remotely throughout the pandemic period. And then I think he was like picking up a few other courses. I don't know. He's just he's just crazy. He's always spending his time learning something. I love it.

Harpreet: [00:10:35] I love that dude. It sounds like my kind of guy. My dad sounds like a very, very awesome person. Sounds like the type of father I hope to become someday. You know, I just really love that story. And I always love hearing about, like, the immigrant story from a first generation as well. Born in Sacramento, California and stuff. But there's so many parallels in the story. There's so many commonalities. Thanks for sharing that and I appreciate that. Speaking of math, man, I was scoping out your background and stuff. I noticed that you and I kind of came from a similar type of background, having kind of walk that actuarial path we're entering into this this data science kind of kind of field. And I'm curious, what was your experience like with those exams, man? Because those things were nuts.

Danny: [00:11:17] I was really lucky in that my SO when I went to university, I ended up getting a scholarship to do the actual studies. And as part of that scholarship we had to essentially do the uni studies, do up to the part two of the exams. So I don't know if it's different in the US and I'm sure there's like parallels, but there's not ones of the technical exams that you do through all the courses and then part twos are the ones where it's more business focused and you need to understand different things about an insurance business or different liabilities and whatever that you need to do for reserving. So I actually I enjoyed the study component. [00:12:00] I didn't do a lot of studying, to be honest, during during my undergrad, we were just kind of too focused on having a lot of fun. But I, I found them okay. A lot of people that I studied with found the part twos, the ones where we had to write about the business really difficult. But I found them much easier than the actual technical exams. But yeah, it was. It was interesting because we were essentially copied on passing the exams. If you failed an exam, you would lose your scholarship. So there was always this drive to do well enough. It was great having like a community of people to learn together because you're all in the same boat together, like you don't want anyone to fail. So everyone was kind of helping out, helping each other out, and that was really great.

Harpreet: [00:12:42] Yeah. Yeah. For us, it was the. I was going for the casualty actuarial society exams. So that was just a battery of exams. And it was mostly. The first exam was just pure probability theory and you have to do it with just I still have my dreaded calculator. Here is a Texas instrument calculator and everything by hand. So I was like calculus by hand and the first several exams are like that. I definitely remember being on a it was called Actuarial Outpost that was like the forums that we used to go to and and talk smack about those exams. Man So what was it about kind of doing that actuarial work that that kind of made you want to leave it behind and kind of move to this data thing?

Danny: [00:13:27] I was really, really lucky in that one of so part of the scholarship, we were also given internships with insurance companies and a few other companies related to the actuarial field. So in one of my internships, I actually had a really great manager and he was good friends with one of the managers from Quantum. And so Quantum is a one of the largest data analytics consulting firms in Australia, and that was where I had my first graduate role after I finished the but in my first internship in like 2000, it must have been 2010, [00:14:00] I learned about the data analytics and the data science at back then, where when I had I caught up with a guy for a coffee and I was just telling him about my background and what I wanted to do. And I think I literally told him, I just want to solve difficult problems and have fun doing it. And he essentially told me about what they were doing in the company. I think at the time they were working with supermarket's data and trying to apply actual traditional modeling techniques to nontraditional industries such as supermarkets and media and different areas. So that sounded something more down my alley instead of predicting when someone's going to have like a car crash and how much money we have to hold and all of that.

Danny: [00:14:43] So which is still really interesting, like I think as a technical problem, it's still really interesting. It just wasn't for me because I wanted to create something new or do something much more aligned to what I what I enjoyed doing. But yeah, from there I, I kind of knew that I wanted to move into data, but I didn't really know anything about it. Like, I remember when I talked to some of the first actuaries and the people who were doing the modeling, I literally thought modeling was like building things with the Lego blocks. Like that was the concept that I had in my head. Like, Oh, it'd be cool if you can build a model of like the city. And all these components would come in and they would kind of match up to things that you want in reality. I don't know. I had no idea what I was talking about. And the guy just like looked at me with like really blank stare. Like, what is this guy talking about? I think I just confused everyone that that was. That was part of my journey into data. So in my first my first graduate role outside of university was with this consulting firm doing data analytics, and I was looking at supermarket's data specifically. So I had like a really, really great upbringing in that sense.

Danny: [00:15:52] But often like after a year or two, I kind of stagnated because I don't know, I just felt that I wasn't being challenged [00:16:00] enough. I'm sure, like many people, feel the same in their careers and they're trying to find the next thing that they want to move to or they want to learn next. So I kind of I was young at the time, but I felt that I learned everything that I needed to know from that area, and I wanted to challenge myself somewhere else. So that was when I started going through the whole data analyst to data scientist transformation. I think having gone through that personally, myself, and come out the other end reasonably okay, I think that's what really pushes me to share more of my experiences on LinkedIn and social media in different places, just to help others who are on that same journey. Because I think back then, like, we might have been doing the same transition across at the same time, and there's just no resources. Like the best thing you could look for was maybe like a blog post here and there. I think KD Nuggets was still around back then, but there was not much else and everything you had to. It was difficult for me transitioning into data science because this is like 2013, 14, 15, like no one knew what it was.

Danny: [00:17:06] There was all this hype about it and people thought that there were magicians and pulling rabbits out of hats everywhere. But in reality, I think people on the ground didn't really know what it was. Was was it different to a traditional quantitative analyst just with different tools? Was it like an analyst without any? Was it an analyst sort of role but with more advanced techniques? That was just lots of different variations and no one really knew. So these days, my my main thing of helping other people out is to not just give them the support and the encouragement and good resources that they can learn from, but trying to dispel the myths and provide clarity. I think having a really clear vision is something that's really important and valuable for anyone who wants to start on anything. So it's one of the things which maybe I grew up doing, but I always try and work, work backwards and then just [00:18:00] almost like imagine what the end state will be and then just kind of step backwards and think about what I have to do all the way back to the present time. And that's really helped me for many different situations, not just in my career.

Harpreet: [00:18:13] Yeah. That feeling of stagnation in your career. I was reading a print article that. And it was. But you made that mention about feeling stagnated in your career. And I was like, Oh, man, I could relate to that 100%. It was the same for me, and I just felt like data science was this exciting thing and it was tough to do. Like I said, find resources and and try to make that shift. So for me, it was about 2017 when I was like, okay, let's, let's try to switch something up. Like it was like mid late 2017. I was like, I can't be this academic statistician thing anymore. There's got to be something else that I could do. And like you mentioned, it was tough to find resources. So I guess when you were like, if you put yourself back to. That that moment when you're said, this is it, I have to make a change. Like, what was the next step after that, that feeling? You're like, okay, I've got to make a change. Like, do you remember what you did next after that? Was there are a lot of you know, I guess. I guess how did you figure out like what it was that you needed to figure out in order to make it in this field?

Danny: [00:19:24] I think the thing that really helped me was to be very open about my, let's call it ambitions or where I wanted to go in life or what I wanted to do. Like I remember early, really, really early on, like when I was during that internship time in like 2012, 2013. I have like a recorded notes from a conversation that I had with like a senior manager and one of the insurance companies. I think I told him I want to be like a CEO of a big multinational corporate by the age of 28. And there's all these like very aspirational goals like listed underneath it. I'll try and find it. [00:20:00] It's hilarious. When I look back to it, I cringe a little bit, but it's like it's sort of having that sort of openness was just something that was built into me. So I'm. To a floor. I'm probably like maybe to open about some things, but having that sort of authenticity, like that's something that's really in fashion now. But it's, it's something that's really important just to be true to yourself, but also to share that with others. Because for me, that was how I found people who wanted to help. And that was probably the the major difference for a lot of people these days. Maybe they're stuck.

Danny: [00:20:36] They just don't have the people to support them either. There's no community. There's no one around them who has the experience to actually give them some questions to think about. Then my big thing, when I was moving from a data analyst role up to whatever the next role was, was just trying to figure out what it was. So I put in a lot of focus on getting clarity for myself, and that included meeting with a few different people. Some of the different people in the company that I was working in were doing some data science, but it was a very small team. They were almost like the crack team that only they were allowed to do data science or machine learning and stuff. So I tried to catch up with them and try and figure out what to do. I still remember I had like a meeting with one of the managers and I was telling him, Oh, I really, really want to become a data scientist. And he asked me questions like, Do you know what a data scientist does? I said, Nope. Like the modeling sort of thing, something more advanced, something challenging. And then from there, I think I also said, Oh, I, I'd really like to start a blog and kind of write about my journey into data science, but I think I was convinced out of it.

Danny: [00:21:43] And this is something that I regret because I was convinced out of it, because I think the the argument was, who would want to listen to your story when you don't have the expertize? Mike. There are so many other people who are writing blogs or whatever and you want to [00:22:00] write a blog and you're so confident that people will actually read your story. And I kind of regret not going ahead and doing it anyway, because in hindsight, I think a lot of people would have liked to have. Read that journey and seeing the transformation that I've had throughout the years and all the different things and struggles that I've gone through. So that's why these days when when my students are going through the same thing, I tell them, start a blog, start documenting. Talk to the camera if you're brave enough and just share as much as you can. Because in a few years time when you actually make it, you would have wished that you would have done that stuff early on just to keep it as a time capsule and to remind yourself where you began. Yeah, it's one of my one of my biggest regrets. But what can you do? Life goes on.

Harpreet: [00:22:43] Yeah. I mean, just kind of speaking from my own frame of reference, man, I feel like you can get incredibly tough, like finding a voice for yourself. Whether it's LinkedIn, media, podcasting, whatever. Especially if you want to try to be unique or a little bit different in some some way. It's like incredibly tough. How do you try to ensure that you've got as fresh a perspective as possible? Do you even need do you even need, like, a fresh perspective as possible? Yeah. What are your thoughts on that?

Danny: [00:23:14] Yeah, the. I would try and clarify what the fresh encapsulates and what it means. So there's like I think there's fresh in terms of like being new, like having a new sort of presence on, on the field or on the market sort of thing. That could be like your personal branding, how you communicate with other people, certain design things that go into whatever you're sharing as well. I try and I try and capture all of these things, but I don't don't focus too hard on anything. If that sort of makes sense. Like I've seen some videos on YouTube when I was starting out on all of my social media stuff and trying to post stuff on LinkedIn and everything. Like I remember watching videos and people were literally like a five minute, five or ten minute video. On choosing the right font [00:24:00] for your design like your logo design I like I didn't watch it. I just looked at the title and I'm like, This is. Whatever. I don't care. I'm just going to do whatever I feel like. And that has sort of been like my motto throughout my whole journey on the social journey and teaching others and all of that stuff. I've kind of. One of the things that you talked about, like being unique and trying to differentiate yourself in such a like a vast ocean of other people, trying to do the same thing is probably the the most difficult thing any social entrepreneur once they they have to do in order to actually carve out an area for them.

Danny: [00:24:40] I remember early on when I was even thinking about doing a business because this was around mid 2020, I first started getting like I was still working at the time I was doing in a contract role in a really great position working on like cloud machine learning, cloud data engineering with supermarket data. And we were building out lots and lots of course systems and automating the heck out of everything and doing everything at relatively high quality. And then, but over time, I just kind of felt that I wasn't having the same amount of impact. And for me that led to, I would say like every time I changed like a career throughout my career, it was due to frustration. So that was like some sort of inner frustration of like I was, I was I was very sure that there was much more I could do or achieve. And that frustration of not meeting up to those expectations that I had led to me trying something different and that's something different was like starting to post on LinkedIn and, and like wanting to become like an influencer. And that was, that was my mindset when I started posting on LinkedIn, like, I wanted to get famous, I wanted to have a big following and whatever I started posting and nothing happened that was like no one was reading my post.

Danny: [00:25:55] There was like crickets and tumbleweeds going everywhere. And that really forced [00:26:00] me to think about what I wanted to what I wanted to give or what I wanted to share. What made it valuable so that others would actually spend the time to stop and read the post and interact and maybe share it and do the other things that I talk about or whatever and whatever is in the post. So. I thought. One of the most important things was having like a design lens to everything. So it's like you can design the best experience ever for someone like yourself. But if you don't think through all the different perspectives and what could happen and what people are going through and their context as they're consuming whatever you're doing. So whether it's social media or your course content or podcasts or anything, having, I think having that design thinking really, really helped just to. It's not even design thinking. It's more just like thinking about how others would experience whatever you're doing. And having that focus then led to me thinking, okay, I need to share stuff that might actually help people. And then from there, I kind of made like a 180 and it was one. There's one book that I always credit this to. It was like, I forgot the name. I always forget the name of the book. I think it's like. Something's Building Your Story Brand.

Harpreet: [00:27:21] Oh, Donald Miller's book. Yeah, I think that's it. Yeah.

Danny: [00:27:24] So but the main thing that really stuck with me is that you don't want to be the hero of someone else's journey.

Harpreet: [00:27:30] Yeah. Yeah.

Danny: [00:27:30] And that really, like, that hit me because that's what I was trying to do before. I wanted to be the hero for everyone. Like, I wanted to show them how amazing I was. Furthermore them all these cool skills and tricks that I've learned, whatever. But that's not that's not what I should have been doing. And when I read the book and started thinking about it, I'm like, Oh crap. I've just been being like an egotistical maniac trying to get myself into everyone's lives. No wonder why no one's listening to me. And then I flipped the script and then I thought about, Okay, if I can, if I can share something [00:28:00] that will help at least one person with something that they're experiencing, then maybe it's worth it. And let's just try that and see how it goes. And from there it kind of snowballed sort of thing. So I made a post like later that week, literally one week after I read the book and had those thoughts about, Oh, is anyone interested in personalized mentorship? I'm happy to have a chat with a few people and see if I can help. And I posted that up like 10:00 pm Sydney time. I didn't even check that, check the reactions of the likes or whatever went to sleep and I woke up the next morning. They were over like 1500 comments and even more reactions with people who are interested. And that's that was like my, I would say the social media origin story back in like 2020 May. Yeah, it was May 2020. So it's just been like a year and a half or so since then. I think I have like 1000 followers or something and then now like I don't even keep track anymore. Like, it's not, it's not, it's not something that I'm too interested in.

Harpreet: [00:29:04] That that feeling of frustration you're talking about trying to do something and I could totally relate to that. And just the reading content is like just screaming as loud as you can into like a digital abyss and just trying to convince the Internet that you exist, minus that it's so difficult. But yeah, building your story. Brand Donald Miller's book, Amazing. He's got this other book, Million Miles in a thousand Years. A Million Miles and 1000 years. Excellent book as well. That kind of it's pretty much story brand but like in action and like a narrative format, it's really, really good. I highly recommend that. I mean, we think I was actually I was talking to you on a loop yesterday. I didn't go live with that with that interview, but it'll be released later. But we're just talking about what it means to be like a data science influencer. I'd love to get your perspective on this, too. What are your thoughts on on what it means to be a a data science influencer?

Danny: [00:29:58] I still I still don't [00:30:00] think of myself as an influencer, like I'm just some dude, like, sharing random stories and trying to help others. But in terms of what, like I view the influences as like your, your Eric Webber's and people of that caliber like I'm. The candle and candle in the wind compared to those guys. But I would. I think people who are really positive usually influences. I think that's two types, right? So there's the ones who are really helpful and wanting to share their knowledge and assist others. And then you've got the influencers who are just kind of resharing, not just in data science, but in general, like for all of like social media and Instagram and Tik Tok and everything that's like original content versus sharing resharing content and forgot the word aggregators of content. Yeah. So I, let's talk about the original content influences because I think that that's a lot of people can get a lot of value by following some of these people. And also I think that's something which I aspire to be like. I'm not too concerned about resharing things which are going viral. I'd rather create something of my own that goes viral, which is much more fun. I think it's it's having a very unique. Brand like a personal brand. So one of the best things I heard about people discussing personal brand is what are other people talking about you when you're not in the room? So it's like similar to in real life we'd talk about reputation. So like your personal brand is essentially your online reputation.

Danny: [00:31:30] And I think people. I don't know. Maybe they try and you can kind of tell when people are trying to craft out the personal brand, like they're trying to design it from scratch and they're putting in a lot of effort to to really almost like force it out without being without it being natural. So I think the best data science influences and influences in general are the people who are just very authentic and they're sharing their true selves. And I think that's the thing that [00:32:00] attracts other people to listen to them, because you can I think as humans, we're very attuned to tell when people are not being themselves like it's it's almost like a tribal sort of thing. Like if you can see someone who's kind of put up a facade, they might be lying or they're trying to get the rest of the tribe to kill you off or something. So I think as humans, we're very adept to identifying those sorts of things. And I think having of course it's like in social media, it's just people on a screen talking about the stuff and it's just words on a screen and images. But I think when we're probably adapting as humans to kind of encapsulate that information, yeah, I think the most successful influencers of our time are the ones who just are relentlessly helpful, positive, and just themselves. Like you can tell that there's no BS or anything. They're just they're being who the who they are and they're not trying to be anyone else. I think that's.

Harpreet: [00:32:57] Really kind of like what responsibility, I guess. Do we have an influencer? I don't know if I can call myself that. You definitely. But I guess what responsibility do we have to these people that are following us?

Danny: [00:33:12] I think one is just to. We have a responsibility to understand. And not just to kind of I would call it. Like shovel or stuff like trying to push our message to everyone sort of thing. Like, I don't know if that's too vague, but it's like when we share something, it's about sharing our understanding of the world as it is, and we want to share that with others, not to force them to pick up our perspective, but to kind of open their minds to what we're thinking about and for them to kind of incorporate it into their understanding. I like that sort of style better because it's not like you must do X, Y, Z, otherwise you won't become a successful data scientist or whatever. Like whenever I see any of those posts, I usually just like click right [00:34:00] through or I'll think angry thoughts and then I'll flick right through. But I, I just like the real like we should foster creativity and creativity and engagement with others. Positivity like never talking down to anyone or talking about how bad like x, y, z sort of thing is. Like, I know I poke a lot of fun in it with some of the names that I make, like bad, not best practices sort of things, but those like best practices come and go with time.

Danny: [00:34:25] So there's only a limited amount of time that you can make jokes about those sorts of things. But I think in general just. We should really be out there to help others instead of trying to help ourselves in a way. Like I know of a few larger names who the social media presence is, their business, essentially. And I know that's really important. Like everyone has to make money, feed their families, buy all the things that they need in life and all that aspirational sort of things. But in a sense, like for me, like I don't know if this is this might be similar for you as well. Like I want my social media stuff and all of the things that I'm doing to help others to not have to be the main source of income. Like, I'd rather I find that when I have that sort of perspective, it really shrouds my mind. Early on, when I was doing all the data with Danny stuff, that was my only source of income. I dedicated myself full time for a little while just to get it, get it up and running and get all the infrastructure. But it was really tough for me mentally because when you're working as a contractor, like every day that you're not working is lost money essentially.

Danny: [00:35:33] And I spent quite a lot of lost money days building out something which I wasn't even quite sure would make me any revenue to begin with. So that was like a really big mental make a leap of faith, I would think. But now coming back into it, after I've done the courses and I started doing more presentations and doing all of the other stuff with Reilly and Pearson and some of the publishing companies, I find the [00:36:00] whole social aspect and helping others and the educational one as. I find it fun, but I don't find it as I don't want it to be my main source of income. My main skill in the data science world is still in the consulting space and helping people solve really difficult problems. And it's really awesome that I've kind of moved back into there originally just a few days a week just to help out some clients with the difficult data problems. But I always wanted to be like as an educator and trainer and teacher, I wanted to be someone who was like. Had the feet on the ground. I wanted to be that grounded person who is still working and they're doing the thing, not just teaching other people how to do the thing.

Harpreet: [00:36:45] Yeah. Yeah, it. It's funny. Yeah. I was talking bad. I hope I don't get canceled for this by the friends, but I mean, I'm launching like an online course, right? Like, obviously I'm doing it because I feel like I've got some specific knowledge that I could share with the universe and the world, that I could teach you things that you're not going to learn anywhere else that will make you successful. But at the same time, it's like there's a lot of people who want to teach you how to become a data scientist, but then they quit their job in data science so they can teach you how to become a data scientist. Let me tell you how great this field that I quit is, so let me help you get into it. I'm just like, Oh. I feel about that. I don't think I'll ever stop being a data scientist, man. This, this will. It it'll. I will always be a data scientist in some way, shape or form, even if it's just me doing algorithmic trading and that's me putting my fucking money around my mouth. It's like I'm like, I'm in this skin in the game data scientist type of thing, man. So yeah. Thanks for sharing that. I really, really appreciate all these insights. Let's get into like this, the mentoring and coaching thing. I want to talk to you a bit about that. So I guess how do you consider the difference between like or what do you consider the difference to be between coaching and mentorship?

Danny: [00:37:54] Hmm. I think of a coach like a sports coach, so they're there to [00:38:00] essentially whoop your ass if you get out of line and if you're doing the wrong thing so you don't build up bad habits. A mentor is more like someone who's I would say it's like someone who's done the things that you want to do and they've had the experience, but they're not necessarily holding your hand. They're just kind of there to if you need support every now and then to clarify some of your vision, some of your goals, maybe to dispel some of your doubts, those are the people who you go to. And for me, like my my personal mentors that I've worked with and had the pleasure of learning from, there are some some of the guys like I haven't reached out to in over a year, but one of one of them actually messaged me after I started doing some of my livestreams and different things on YouTube where I was sharing a lot of my knowledge. And they messaged me back to say, Oh, I saw some of your videos and it's amazing what you're doing. You should continue doing it. And that just made my entire year. I think it made like all of the struggle that I faced before up to that point, almost just little things like that. And I think that's where a mentor is really, really valuable that like I would say, it's like a mentor and data science almost, or a mentor in life in general is like a coach for your soul where if you like, whenever you're down, you can go to them and they'll be able to help you in some shape or form.

Harpreet: [00:39:27] I like that the definition I mean, because I'm kind of in this mentor thing mentorship game a little bit but I like I feel like the mentor is like someone just shares their knowledge skills. Here's our experience and we're just trying to help people grow and develop. And coach is someone who is providing guidance to a client on their goals and help them reach their full potential. By the way, shout out Kenji is in the audience, our good friend Kenji Ken. It is good to see. Good to see here, my friend. He joined right in time. He said he's glad he got here before it ended. And I'm like, Oh, [00:40:00] we're just getting started, man. We're just getting started. Ken can ask the question that I'm going to just put a little twist on. Ken wants to know, How do I find a mentor if no one has done the things I want to do? I think that is a very good question. But let's first answer it. You know, this question maybe like an easier version of that question before before you get to Ken's question is, I guess, can you share some tips with the audience for how we can go about finding a mentor? Because, I mean, I know you get the messages as much as I do in in LinkedIn or whatever. Like, can you please be my mentor? And it's like, man, like, I get literally I wake up to 30 messages like this day and I can't be everyone's mentor, but you don't necessarily need me to be there. I could be a virtual mentor. I just. Listen to what I'm talking about. Coming to a podcast, a happy hour. Many different ways. What are your thoughts on that? Like, how can somebody go go and go about finding a mentor?

Danny: [00:40:54] I actually think it's it's really difficult to find a mentor in this virtual world that we live in now. It's like it's paradoxical, right? Because we have so much more options to connect with people. Like, I can just message can I can message you and ask you guys to be my mentor. But it's almost like because of that ease of access, there's just too much demand for people. People's time to do that. So I'm in the similar boat where everyone's like, I get messages through the wazoo to to be their mentor, essentially. And I'd love to mentor everybody to get me wrong. But there's just we just have so much time in the day that we can actually talk to everyone. But I think for people who are looking for mentors, probably start first with your local community, the people who are within your area or within your company even or within your family, friends and family circle to try and. Ask for guidance. I think it comes back to being, I would say, vulnerable enough to know that you need the support from someone who's had that experience. I think that's the first step.

Danny: [00:41:58] It's like acknowledged that you need [00:42:00] you need help. Then go out and try and find people who fit the bill to provide you the help. And then you have to experiment, essentially. But I think the in terms of finding people who've not done the things of finding people who have done the things that you want to have or you want to do in your mental. That's much more difficult. I would challenge Ken. Well, maybe not, Ken, but like people who have that sort of mindset to say, have a think about exactly what you want to achieve. And if you can't find someone who's done at least a slither of something that you've done before or something that you want to achieve, then I think that's something wrong with either your goal or maybe your vision is not clear enough, or what you want to achieve is not clear enough. Because my philosophy is that you can learn something from anyone and it doesn't matter of seniority, age, gender, race, whatever. It doesn't really matter. There's always something you can learn from someone else.

Harpreet: [00:43:00] And that was I'm rereading, actually reading for the first time, James. James Altizer his book, Skip the Line. By the way, if you're listening, James Altizer T-shirt was on the podcast. Go check it out. Great conversation. But in that book, he talks about that. He's talking about what you're talking about is the book. The subtitle of the book is like the 10,000 experiment rule. So just experimenting and doing different things. But there's, there's this other interesting concept about like borrowing hours that was really interesting. So you can borrow ours in a number of different ways. So if somebody hasn't done the thing that you want to do, then look for something that's adjacent to it and maybe find out how they did that thing and see what elements of that thing. That's not exactly what it is that you want to do, but very similar to it. What elements from that can you take and apply it to this new thing that you want to do? I think that's kind of like the essence of. Creativity as well as finding different things that on the surface of it don't look like they belong together. But when you put them together, it [00:44:00] actually gels quite nicely. You get something, something new.

Danny: [00:44:02] There's a term for that right now. I think it's like the adjacent possible something.

Harpreet: [00:44:07] Yeah, yeah, yeah. Right. Yeah. I think that that might be the actual term. Yeah.

Danny: [00:44:11] Adjacent possible something like that where like a lot of new inventions and stuff have come out of like an adjacent field that may or may not be related. It's just someone had the intuition to make the connections and connect the dots, and then that led to something else. I think people can take a lot of inspiration out of that same concept and apply it to their own careers and lives as well.

Harpreet: [00:44:35] I want to come back to this point about borrowing hours for people who are maybe transitioning into data science from from from a different field or an adjacent field. But I've got a selfish question here. Continue on this mentorship thing, because, you know, I'm wondering if you have any advice for people who may have accidentally found themselves as a mentor, me, someone like me, who's I don't know how the hell I became a mentor, but it happened and it was accidental as hell. So do you have any tips on on how I can be a better mentor?

Danny: [00:45:03] I'm sure it wasn't so much of an accident more that it was it was meant to happen. So you've just fallen into the into the right path, perhaps? I think the most important thing is that now for for the data with Danny stuff, I've got almost 1500 students on board now, which is and as part of that program or like that community actually offer up mentorship. But it's in a way where how do I put this in a nice way? I don't really believe in people paying for mentorship, if that makes sense. It's like if you're paying for mentorship, it's coaching. And coaching is not mentorship. I think we've talked about this just recently, right? So the I think of mentorship is something that it's like it's an investment of time, not so much of money. So for for example, I've got so many students, I only offer mentorship [00:46:00] to the students who are most engaged in the community. So we use discord. So there's like different levels and different coins and different things that people can do to to earn coins. And I exchange the tokens for my time essentially. So I've got X amount of tokens will buy you half an hour of time. We'll do like a video conference and I'll answer a few questions and things like that.

Danny: [00:46:23] But as a mentor, I think as, as you get more and more people and you kind of scale out, there's, there's no way that you can scale yourself individually. So thinking of some of the other things that I've worked on is to bring on some of my students as community mentors and help is in the data with Danny Community as well. So a good friend Abe as well is on there. So I, I really wanted to so for me it's like I want to mentor the people who have a vested interest to mentor others in a good way. So it's like, I want to mentor the next generation of mentors. I'm not going to let the buck stop with me. So I only focus on the people who throw the right energy. They have the their mindset is great. The learning, the things that I've been teaching in my course and asking lots of questions and interacting with other students, those are the people that I want to mentor because I think there's this continuation in that for me, I don't know if it's like the worst thing that could happen, but it's more like. I could. I could mentor someone. Maybe they pay me for it.

Danny: [00:47:29] They pay me like a few hundred dollars an hour or whatever it is, the mentorship. And then I do one session with them and I never see them again. I never hear of what they do. They don't update me. They don't ask further questions or anything like that. It's like, Yes, I've traded time for money and I'm okay in that. But in terms of like energy flow and time investment, because when you talk and mentor someone, you're investing not just your time but also your energy and you want to see them do well, otherwise you wouldn't have the conversation with [00:48:00] them in the first place, right? So I think having that sort of mindset and really connecting with anyone who's your mentee is really, really valuable, but always safeguard your time because you always need the right you need the right amount of time to help yourself so you can have more capacity to help others. I'm I still learn this myself all the time. I am one of those people who just want to give, give, give, and there's no time for me to do whatever. So I'm slowly re learning how to get more balance in my own life, so I'm probably not the right person to ask for advice.

Harpreet: [00:48:34] A lot more generous to me, man. Yeah. I mean, I found myself as was not intentional. I never was like, yes, I'm going to be a mentor. That's what I want to do. It was like I joined one of these programs by one of those type of people to talk about whose business this is. Personal brand. Oh, great program. I learned a lot. It set me on the right trajectory for my career to well worth every penny I spent for it and the investment I got back for being a mentor has been crazy, but it just happened accidentally. By doing what you said was I was just really helpful around the community and just in the Slack channel. People had questions. I'd ask how to answer the question like, All right, well, this is something you can easily Google. Let me Google it for you and gain the knowledge and help you at the same time. So I continue just to do that. And then he brought me on as mentor, principal mentor, head mentor, whatever. And it's been like a. Woodside has a pretty, pretty well to that. But yeah it's just it was accidental like you know definitely not as a as I don't know I'm being authentic, I'm keeping it real. Like I'm not as generous with my time. Like I just that's the thing that I guard the absolute most, like I just did. My time is the one thing in life I will never get back, ever. So I just started that shit so fucking preciously. Like, the only thing I have in life is my time. Yeah.

Danny: [00:49:53] Sometimes I try and do like. Like a mental exercise of time travel. So it's like, okay, if I spend half [00:50:00] an hour with someone to try and help their problem or whatever, how will I feel at the end of it? Will I feel that I've made a good use of my half hour? Have I helped the other person? And they're like some of the heuristics that go through in my mind before I accept or decline. Whatever invites get thrown my way. Of course, at work and when you're working with clients, it's a little bit different because you kind of have to say yes. But in terms of yeah, sometimes I just feel that intuitively, you know, whether something is a good use of your time and deep down, like you'll know after whatever time you've spent, like, why don't I just do that? I should have done something else. Like, I could have went on a run for 45 minutes or something. I don't know, something like that. And even especially for you with with a family and children, like it's like your time is not just your time as well, it's your time with your family. So it's even more valuable.

Harpreet: [00:50:53] In the comments as you can scale yourself through videos as some expert he would know. Real quick though, I mean, we got like ten, 15 minutes left, but if you're okay to go over so so am I just if anybody wanted to find out about anything that you're up to any time, place, like an event, live event, any of these type of activities that you're up to, where can they go to to find that stuff?

Danny: [00:51:15] So this is on my this has been on my back log to do for like a few, a few months now. But I wanted to have like my own personal website with like all of the things that I'm doing in one place. But I just haven't got around to it in terms of all my social media stuff and the different things I'm going live. I think LinkedIn is probably the best place for all things related to my course. So the data with Danny Serious, I need to do a better job of updating what's going on, but we're essentially starting live training, so we'll be teaching my entire course from start to finish over a series of weekends. So 90 minute sessions, I'm doing two sessions a weekend because I hate it when I miss a session and I can't join live. So I'm actually just going to slot out to different times to match everyone's time zones every week. So I'm starting that in 7th of [00:52:00] November six, 6th of November, depending on what time zone you're in. I think I made a few announcements on my LinkedIn page, but yeah, I'll I'll probably do some more posts coming soon. But I think at the moment it's really difficult to find out what I'm up to. I don't know if it's by design or whether it's just kind of happened, but I, I've also been posting less on LinkedIn. I used to like post like crazy like at least once a day to keep the links up and whatever. But now, now that I've started working on more consulting projects and also like I've started like a new workout health routine as well, like I'm going back into my kickboxing and doing Muay Thai as many times as I can a week and going on daily runs.

Harpreet: [00:52:41] And like you do a lot of deadlifts, you probably do a lot of deadlifts. I can tell you I did traps there, man.

Danny: [00:52:46] Yeah, I, I've been I was doing powerlifting and Olympic weightlifting for many, many years since university. So these chaps are probably like all from power cleans and and shrugs and stuff.

Harpreet: [00:52:59] On top of it. There you go, people. If you guys want to find any stuff, you have nowhere to go. But just catch them on LinkedIn.

Danny: [00:53:08] On LinkedIn.

Harpreet: [00:53:09] So let's get I want to hear about this love of SQL. How did this how did this happen? Man, is this something that you've always just kind of like enjoyed? Like has SQL always been your favorite part of the entire data science ecosystem? Taught me a little bit about just this. How this deep, deep love of SQL happened.

Danny: [00:53:27] Yeah, sir. Sequel was my first proper thing that I had to learn on the job. So working in the data field, we had to use databases, and SQL was the first thing that I had to figure out. And I wouldn't say master, but at least learn how to use to get the data that I wanted and then we would throw it into whatever else thing that we were using. So I think at the time we were using SQL to hit the database. Then we would use like we would just dump it out as CSV or whatever and then do some Excel or whatever. [00:54:00] And then a lot of the automation that we were doing was in SAS. But the thing with the SQL is that I just found it really elegant the way that you could just, Oh, I want these columns from this data set. I want to join it this way. And I just liked how logical it was. And I realized that my. Early on when I started learning from school, I learned from one of my mentors at the time who was my senior analyst, and I literally like my first day in. I said to him, Oh, well, this is the school thing that we have to learn. Can you please share with me the hardest thing that you've written in the last month or so, and I'll try and figure it out. And he sent me the query.

Danny: [00:54:42] I literally printed it out on paper. I used to highlight it to try and match the brackets and all the different things. It was like a crazy nested subquery looking thing because back then we didn't know any better. So we just we wrote like huge views with 20 sub queries and it was, it was a nightmare to try and understand, but that was sort of my initial trial by fire learning SQL and every single role that I've moved to after that, having really good SQL knowledge and having been able to just work on really difficult challenges and problems and use sequel to answer them has been like the cornerstone of my whole career, I think. Of course, I've picked up the other data science tools like doing Python visualization, Docker containers and ML ops and whatever. All of those things were really important. But the thing that's been kind of shared between all of those different lives that I've lived within, the data ecosystem is like. Equal is still the de facto way that people deal with data no matter what role you're in. So if you're a business analyst or a data analyst, you want to do things in the database and SQL. And then if you wanted to then hand it over to a data science team so they can help you build some models for it, they'll ask you for the secret script so they can get the same data that you were using [00:56:00] to analyze.

Danny: [00:56:01] And it goes on all the way through to the full production ization process, where having SQL queries makes it really easy for the engineers to understand, because it's just part of the toolkit that everyone needs to know. And of course there's different levels of difficulty and different skills that you can have in SQL. But in general, like for me, teaching SQL was the first thing I wanted to teach it as a base for problem solving. Because he can almost do everything that you that you really need for all the computational challenging data problems, you can do it in SQL. That might be some challenges in different things, but you you don't necessarily need to go out to an IRA or a python to do some more. You can implement it directly there. And I wanted to kind of share that. I would say passion, but also like some best practices, how I format my SQL code so I can read it easier, what I recommend to the people that I work with and all of those different things, it just seemed like a very natural thing for me to share my knowledge because I really think if someone was to come in to a brand new data role without any experience or anything, they should definitely learn SQL first and maybe like some Python at the same time perhaps.

Harpreet: [00:57:18] Even like not across I think tech in general it in general scales like the to everybody existing to work with data you don't even necessarily need to come from like you mentioned business analysts but anything in tech. So I mean going back to this this notion of borrowing hours, right. Like we mentioned, there's transferable skills that people have. I guess let me rephrase the question I'm trying to ask here. It's, you know, can we draw the line somewhere? Let's just hypothetically take somebody that's a data analyst, right? Can we draw the line between a data analyst and a data scientist? And and you point out that skill on that one skill. If you just had that one skill right there, if you knew this one thing, you'd be a data scientist. Is there something like that or is, [00:58:00] you know, borrow ours from from other parts of our lives to be successful in data science? Does that question make sense? Man, I would.

Danny: [00:58:08] I can give you like a meme.

Harpreet: [00:58:10] Answer Yes, it probably will be acted out then.

Danny: [00:58:15] Just like Python. So the joke is that if you're a data analyst and you know, SQL and Excel and maybe, you know, some Tableau or different things, if you just know the basics of Python, put data scientist on your LinkedIn profile, you'll be fine. Normal? No. But these days it's like. It's just a joke, guys. But the I think Python these days is actually really useful skill, especially for data science, because a lot of things are moving towards that. I would think that a lot of people who are really serious about analyzing their data usually gravitate towards are because it's just easier to analyze and visualize and present your findings in a very structured manner, like using markdown and notebooks and different things. It's just really easy to do. Whilst Python, the support for those sorts of things is still coming in there. Now I've got like stream lit, which is really great, like and Jupyter notebooks and different things, but it's the different things. So usually in, in my experience anyway, we'll be using Jupyter Notebooks to hack around to try and explore a few things and almost have it like a notebook, like a scientific notebook where you're just trying a ton of different things. You have no idea what's going to work. And then when it comes time to creating whatever you figured out into an actual application or something that you want to deploy, usually you need to do it at a relatively high level or high level of programing skill, but a very low level of coding ability.

Danny: [00:59:43] So you'll need to go into like traditional ID and build modules and do all that sort of stuff. But it really depends like these days, like I think the term data science is just so broad and people are there's always incentive for people to rebrand themselves as a data scientist or machine learning engineer just because [01:00:00] that's that's what brings more money. And deep down, like, that's why we're working, right, to provide for our families and all that sort of stuff, but to also like solve challenging problems and have a great time whilst you're doing it as well. So I think that yeah, probably for anyone who's tuning in and they're looking for like that one killer skill to like turn them into a data scientist. I wouldn't say like learn Python and you'll become a data scientist. I think it's just having my. But not sounding too good. But it's like you should learn how to learn anything. That's probably like, if you can do that, you can can become whatever you want really, like, and you.

Harpreet: [01:00:40] Can change with the times, right? You could change like Monty Python right now is the best language for machine learning. Right. But it could be maybe rust in a couple of years. Right. That could change, right? Exactly right. It could change closure if you started some really crazy stuff with data. Thanks for sharing that man. And says Dead Lives with Danny. That's what I'm talking about. Shout out to Matt Bratton is in the building. So. I guess the question doesn't.

Danny: [01:01:05] Ask, but can I ask you a question?

Harpreet: [01:01:07] Yeah, definitely. Yeah.

Danny: [01:01:09] So I've always thought about doing a podcast, but I just never found the right concept. Like, for me, I'm very I would say, like I'm very conceptually driven, even though I've done things where I just kind of go for it and then I try and figure it out. In my intuitively, I feel that a podcast is not something that you can like go into and then kind of change halfway through sort of thing. I think it's just like like I don't know if you can do that, if that's the thing. Maybe, maybe I'm just closed minded, but I feel that I need like that killer idea that's unique to me and something that people will listen to and people will enjoy. And I just haven't found it. And I think that's the thing that's been kind of blocking me on that because I've got I've got all the equipment ready, like I've been ready for many months. Maybe I need some more like [01:02:00] reliable cables. But apart from that, like, yeah, I'm ready and I know all the benefits that it will provide for my, my personal and professional, my careers and lives and stuff. But I just haven't the drive to to go further because I haven't found it yet.

Harpreet: [01:02:16] Yeah. I mean, I just have this intense need to just always be myself in any medium. Like, that's how I talk. Like, I've got no filter that just be myself. And I never wanted to be in a situation where I had to feel like I just couldn't be myself, right? So I felt like the podcast would be a good expression of doing that. And I started doing the podcast and I first did it. It was about sharing the journeys of people with data science. And then I did about 40 episodes like that, and then I just switched it halfway through and I was like, Yeah, that's cool. Like, I mean, Kinji does a better job than I do of finding out the journeys of people in data science. I mean, you know, super data science, they do a better job of that than I do. I was really into personal development, so I said, All right, so I'm just switching it out. Rebranded myself as the only Self-Development Personal Development Podcast for data scientists, and I did that for a while where I just talked to not only data scientists, but I talked to a bunch of people who've written books that are in that space that I'm that I'm about and popped up with with the data science happy hours because I figured that would be a good way to keep the data science in the podcast. But more recently, like I've been shifting more towards, like I said, it wouldn't be completely authentic to me. And my interest and my podcast reflects that. Like your listener on my podcast is not for you, is for me entirely. For me, I do this thing selfishly because I talk to the people I want to talk to.

Harpreet: [01:03:42] I talk to people I think are cool. I want to get to know them, want to have this conversation. So I do it entirely. For me, this podcast and part of that is now exploring my interests. So that's why I bring out a lot of authors, because I read a lot of cool books and I want to talk to the people that wrote the cool books. And so very slowly now moving into [01:04:00] a direction where it's most likely going to be mostly for whatever the next, however long it is that I'm into this chapter will probably be a lot of philosophy, a lot of physics, a lot of science. So I'm reaching out to people who are writing books like that or people who have a voice in that kind of in that kind of space. Obviously always keeping the data stuff in it as much as I possibly can there, talking to my friends like you. And just last week, I spoke to Christina. Next week I'm speaking to David Langer like, you know, keeping keeping the data science people in it, but more just as an avenue for me to really, truly explore the things that I want to explore and share the conversations with with people. So that's just kind of how I keep it authentic. I've got no qualms for telling people that it's not for them like this podcast is for me. I just happen to be a data scientist, so I could put data science in the podcast title and not feel kind of about it. But yeah, that's. That's kind of my approach to it. Mm hmm.

Danny: [01:04:58] Maybe I'll. I'll take that in and have it think I've just been just been stuck in this position of, like, not wanting to start and throwing up, like, I would say, almost irrational barriers to it. Yeah. I also want to. Oh, you.

Harpreet: [01:05:11] Know, I gonna say this. I mean, if you're feeling that, then nobody, nobody says you have to have a podcast, right? Nobody's forcing you to have a podcast if you're feeling that kind of way. I think that's indicative of if something anything I don't know if I'm going to commit to this because there's nothing worse than saying you're going to start a podcast, putting it out there looking guests, and then doing three or four episodes and just dropping it like you don't want to do that. That's that's even worse. Maybe you just like coming on to podcast and talking to people on their podcast. That's, that's cool, man. That's one way to kind of get that out there. And then when you get your website up, you can say, Hey, people, listen to these episodes. If I was in your situation, I felt that like the real hesitancy to like even my personal life that happens with with things that present themselves to me opportunities. And if it's something that I continually put off. [01:06:00] So I've got this like weekly calendar thing and my weeks out and I look back and I see the stuff that I don't get done over the course of three or four weeks. Fuck it, that's not a priority. I'm not doing that. Not, not do it. There must be a reason why I'm not doing it. Because I don't want to do it. So that's kind of the way I would think about that. But if if you really, truly want to do it, Danny, you would have done it by now. We'll talk about.

Danny: [01:06:23] Yeah. 100%.

Harpreet: [01:06:25] I'd listen to it, though. You got a nice, soothing voice.

Danny: [01:06:27] Oh, thanks, man. I wanted to ask you, how did you manage to get an interview with like Robert GREENE and James Altucher? They are like the authors that I've been listening to for years. Yeah, well, reading their books for years. It's amazing that you've managed to grab them onto your podcast.

Harpreet: [01:06:47] I mean, a lot of people on like I can't even believe. Yesterday I interviewed Marcus du Sautoy. Oxford professor wrote creativity code been, you know, BBC documentaries and all this stuff. But Robert GREENE actually seduced him. I did. I got him on. I messaged him on some social media platform and he said, Reach out to my assistant. And then I lied to his assistant and said, Oh, hey, Robert GREENE. You know, we're chatting back and forth. And he said he'd love to come out with a podcast and told me to reach out to you to schedule something like he didn't say any of that shit, but he just said, Oh, you pass this request to my secretary of my assistant. But I played it off like I actually got the interview with the assistant and then James Altizer I just kept sending him ten ideas a day and ideas a day because that's his thing. So I sent him ten ideas a day and said, Look, I'm going to keep sending you ten ideas a day for ten days. At the end, you would come on a podcast. Great. If not, no hard feelings. And then he said, I'll come on your podcast. So that worked out epic. Yeah. I've had other cool people, man, like Annie Duke, who wrote a book that changed my life, thinking and bets. That was a great episode. [01:08:00] A number of people ask, Crazy. How many? I just reach out because there's no downside. There's no downside whatsoever. There's nothing but complete upside. Worst case scenario, I get no response. I would have gotten no response if I didn't send the email anyways, so no big deal.

Danny: [01:08:18] It's awesome, man. You're an inspiration.

Harpreet: [01:08:20] Thanks, Matt. I appreciate that. Oh, yeah. I mean, I remember listening to an interview with you actually speaking a podcast. I was listening to an interview with you on things called The Humans of AI Podcast.

Danny: [01:08:30] Oh, yeah.

Harpreet: [01:08:32] Who the host was on. Oh, okay. Yeah, yeah. Yeah. He's that. Your mentor, if I recall correctly, you guys had worked together something you kind of helped him on the come up. How are you talking about that? You're talking about that idea about building an app to make billions, but then back then, you didn't take too much action. What's what's your take on the importance of taking action on an idea you have in your mind there?

Danny: [01:08:59] I would say my whole social media journey and the whole thing that I've done with data with Danny was just taking it was just brute force, relentless action. Kind of like the whole concept is like jumping off the cliff and not knowing if you'll survive and then you're trying to build a plane on the way down. That's essentially how I felt for the whole my whole entrepreneurship journey has been like that. I'm pretty sure it's not going to stop feeling like that. But there's I think there's a general rush about doing those things. It's much harder than working as a data scientist. Like I found that running my own business and doing all sorts of stuff has challenged me much more. Like I probably would have had like accelerated growth over the past 1218 months compared to when I was just working building models and doing analysis and different things. Just the amount of decisions you have to make day to day is ridiculous. Not just like, am I going to eat this food or eat that food or whatever, but more challenging [01:10:00] decisions like do I focus on this for the next month or do I focus on another thing which could be better? How do I allocate my precious resources of time and energy to solve as many things as possible? Just yeah. I think the only thing to help you do more of those things is to take lots and lots of action. And I should take my own advice and take more action for my podcast. And Ken's probably on my case to put more YouTube videos on as well.

Harpreet: [01:10:27] Yes, they. How about YouTube videos in the comments there man. Yeah. Taking action do like that's that's something that didn't click with me until much later in life. Like James Altucher says, you know, people say that ideas are a dime a dozen, but execution is everything. But there's not exactly true because there's execution type of ideas that you need to come up with. I'm butchering his idea muscle thing, but yeah.

Danny: [01:10:54] It's like you can you can take action. But if it's not the right type of action, it's still not going to help your ideas in that sense. I know this from firsthand because it's like when I when I procrastinate, I go and cook something. Like, I try and, like, try a new recipe or something or whatever. Because I love cooking. Or I go out to the plant shop to buy a new plant just because because I don't want to do whatever I'm whatever I need to actually do. And then when I get home, like, crap, why do I do this?

Harpreet: [01:11:22] But when you do that, when you take those type of breaks, is it is it the case that when you come back to the work, like maybe you had like a breakthrough or an insight or you just flow's a little bit smoother after that. Is that is that the case during these type situations?

Danny: [01:11:37] I like to think that that's the case, but I don't know if it's just like my backwards rationality. It's like, Oh, I took a break, so now I'm more productive, I feel good.

Harpreet: [01:11:47] I guess we rationalize everything that we possibly can as humans. Right. Let's go ahead and do one last question before we go into the random round, which will be a lot of fun. We'll open up a random question generator and do all that stuff. But it [01:12:00] is 100 years in the future. What do you want to be remembered for? Hmm?

Danny: [01:12:05] For sharing his knowledge with as many people as possible and impacting lots and lots of lives.

Harpreet: [01:12:11] Absolutely. Love that. That's definitely happening, man. That is that definitely happened.

Danny: [01:12:14] Oh, many things. Funny story about that, actually. So when I when I first started making the move across to data science actually went to my went to a coffee shop and I sat down and did the exercise of, okay, you're on your deathbed. You have like your your families around you or your grandchildren, whatever. What do they want to remember you by? Like, what do they what do they want? I have like all of my friends and stuff with their. And the same thing popped into my head straight away there. It's like, oh, he was just very knowledgeable. Dude wanted to help a lot of people and he did good by others and that was it. And I didn't really care for too much else. So yeah, that was almost ten years ago, maybe more than ten years ago.

Harpreet: [01:13:01] That's it. It sounds simple, but it's hard work to do that as consistently as you have on as large of a scale as you have. So definitely well on your way to if not already achieving that. Danny, thanks for for all that you do. Let's go ahead and jump into the random round. First question is, at what point did your meme game get so dank?

Danny: [01:13:23] Oh, but funny story. Back in university I actually ran a meme page for my uni, but it was not very good because I just like I wasn't very good at memes back then in 2010. So I just, I remember making a few memes and just laughing it up myself and then I thought, Well, if I'm laughing at it, maybe someone else will laugh at it. And then just started posting. But originally when I started posting memes they were really mean memes because I just dealt with a lot of like bad stuff at work, like just like data scientists doing crazy stuff. And I didn't like it, so I just like, don't do this, [01:14:00] blah, blah, blah, whatever. So, but then over time, my means became a bit more, I would say, like pointing at things which were wrong with the whole industry as a whole as opposed to like people's behavior. And I think that's what kind of changed it. So it's like people thinking that you can become really great data scientists if you only have deep learning skills, but you don't have data analytics, analytic skills or something like that. Like when I focus more on those broader issues, it really helps my meme game. But I stay up to date with my means by like scrolling on Reddit and different things.

Harpreet: [01:14:36] So I love that man. I tried to come up with memes, but I'm just not hip enough, man. I'm just not definitely.

Danny: [01:14:45] Definitely hip enough.

Harpreet: [01:14:46] So in your opinion, what do most people think within the first few seconds of meeting you for the first time.

Danny: [01:14:55] These days, it's like, that's a cool mustache. Um. I don't know. I think it's usually I get when when little children see me for the first time, though, their eyes light up because I'm just always very smiley. So they say I have like a smiley personality. So like all the kids kind of like follow me and animals do the same thing as well. So, yeah, I don't do anything different. I just kind of go along doing my daily business.

Harpreet: [01:15:21] Yeah, you have the happy Buddha look, man. That's. That's true. That's true. What are you currently reading?

Danny: [01:15:27] Oh, great question. So I just my last book I read was by Gilbert. I can never pronounce it. Oh.

Harpreet: [01:15:34] Yeah. Friend of the show.

Danny: [01:15:35] Yeah, yeah, yeah. So that was that was actually the first book that I read in over a few months, actually. I sat down and read it in like 90 minutes nonstop. I didn't do it as exercises, unfortunately, but the exercise is really good too. I highly recommend it. But that book was great. It felt like it felt like it was talking to my soul, but also telling my own story to myself, because I experienced a lot of those things about like [01:16:00] awkward conversations with people or like not setting the right boundaries and not changing and updating your behavior. So that that book really spoke to me in that sense. Really, really, really recommend it to everyone. And another book that I read recently was like a matthew Riley fiction book. So it came out I don't know if you've heard of Matthew Riley is like famous Australian fiction, like action fiction, novel writer.

Harpreet: [01:16:25] Yeah, it sounds familiar.

Danny: [01:16:26] You'll love the book, Samantha. It's like when you're reading it, it's like a Hollywood action movie. Like, playing in your head is really, really good writer. We just released, like, the final like the final book of, like, a series about like an ex Australian SAS dude who goes and saves the world from all these like crazy Egyptian God type stuff, like all this mythical mythological history stuff. Oh, it's amazing.

Harpreet: [01:16:53] I love mythology. Ancient mythology is amazing. Via shout out to Gilbert I Kaylin Boom, friend of the show. He was on the podcast in the early days around the first people.

Danny: [01:17:04] Eyes the legend.

Harpreet: [01:17:05] Really great guy. What song do you currently have on repeat or stuck in your head?

Danny: [01:17:10] Oh, I've been lately because I've just been coding. I can't have any lyrics, so I just listen to like lo fi, lo fi, hip hop. And I always have like lo fi hip hop girl playlist.

Harpreet: [01:17:20] Oh yeah.

Danny: [01:17:21] Or whatever. Like the I would say anything by an artist called Avi E v e. It's just like super chill. You can listen to it any time. Puts you in a good mood.

Harpreet: [01:17:34] I highly recommend you check that one out. Yeah, I've been listening to a lot of like, I'm writing code all day. It's hard to listen to stuff with lyrics. They'll start typing that into my code. So Tom IVs put me on to it. Monster cat silk. That's the name of the station. But there's a they've got multiple live stations, my favorite ones like the Progressive House, 24 seven station.

Danny: [01:17:56] Oh, nice.

Harpreet: [01:17:57] Yeah. So good. So this is the actual random question [01:18:00] generator. Let's go ahead. Pull this up. First question. Who inspires you to be better?

Danny: [01:18:05] Oh, Harpreet. And Ken.

Harpreet: [01:18:09] What's the best piece of advice you've ever received? Oh.

Danny: [01:18:13] Make a good first impression.

Harpreet: [01:18:15] Who is one of your best friends? And what do you love about them?

Danny: [01:18:19] Oh, one of my best friends. His name is Justin. We we hardly have a chat these days, but every time we catch up, it's like we've never had any distance. So shout out to Justin.

Harpreet: [01:18:29] Yeah, legend Justin. Yeah, it's awesome, man. Love friends like that. Let's do one more here. If you were a vegetable, what vegetable would you be?

Danny: [01:18:40] Potato. Maybe a sweet potato.

Harpreet: [01:18:44] Danny, how can people connect with you? And where can they find you online?

Danny: [01:18:48] Yep. Connect with me. I'm Data with Danny everywhere. So LinkedIn, Twitter, Instagram. I think those are the main things. Maybe I'll do a tik tok later. I don't know. Find me. Find me on the data with Danny Ecom website that's currently we've got the serious SQL course. If you want to join me for live training for the next few weeks coming up, you can go ahead and do that. I think the price is $49 US and $29 for students. You can go on the website and figure it out how to how to contact me and all that stuff. But yeah, just be free to be free to hit me up on any of those things. If you join the course, you also get access to me on discord as well. So I discord is pumping. It's very, very fun. Yeah, that's where you can find me easily because I tend not to reply to LinkedIn messages because I got I got slammed by my new think I put in like a new job and then I put in like my, my birthday and then my inbox was gone. Like, I don't even see how tweets messages anymore. They just disappear.

Harpreet: [01:19:53] Right in there. Danny, thanks so much for taking time out of schedule to be on the show today. Matt, appreciate you being here and I appreciate you [01:20:00] staying staying over schedule. So thank you so much for your time.

Danny: [01:20:04] Norman It's my pleasure. Thank you so much for having me.

Harpreet: [01:20:07] My friends remember you've got one life on this planet. Why not try to do something big? Here's everyone.