HH62-17-12-21_mixdown.mp3-from OneDrive

Harpreet: [00:00:09] What's up, everybody, welcome, welcome to the artist Data Science Happy hours, Data Science, Happy hour! It's Friday, December 17th, 2021. This is the last Data science. Happy hour of the year. Man, it's been a good year, man. I know a lot of you all have done some amazing, amazing things. Shout out to everyone out there just leveling up in every aspect. I'm so, so happy for you guys. Everything has done this year and then all the nice. It's a lot of big things happening with the old man. It's it's really inspiring to see the moves all the guys are making. So congratulations to all of you out there. @theartistsofdatascience been part of the office hours and part of as part of this whole adventure over the last year and a half or so. Thanks for thanks for being here, man. I appreciate all the AIs my friends, the last happier of the year when we keep this one short. I got to get to a hockey game and about, you know, half an hour or so. So we'll keep this one to just a quick half half an hour. I just wanna say thank you guys for being here. Thanks for always just hanging out and tuning into the podcast. A lot of big milestones this year, man across the well released. Not only not only did we release episode number one hundred, but we also released episode number two hundred in this year celebrate the one year anniversary got one hundred thousand downloads. Some big, big things happening for the show. I mean, not big. It's just, you know. Yeah, there's good, good things happening, but I couldn't have done it without all of the support and love you guys helped, so thank you so much for four for being here for this ride. Russell, how are you doing, Matt? How are you doing, Monica? What's going on? A. Eric, all the guys in the building, they're super excited to see all of you guys here. Well, happy. Happy. I guess. Early Christmas. Happy. Happy early new year holiday season to you all. [00:02:00] Monica, what's going on? How's your week been?

Speaker2: [00:02:02] Good. I we spend really good. I passed the exam that I was talking about last night, so congrats.

Harpreet: [00:02:09] Congrats. Oh, how was that experience? Was it an incredibly difficult exam? So, so give us the context again. What was like the exam for what kind of skills was it testing and how did you

Speaker2: [00:02:22] How did you study? Yeah. So it was Fair Foundation's given by the open group. And really, it's around risk qualification. So I'm in cybersecurity currently as a risk behavioral analytics pro product owner. Very mouthful. Big mouthful. So what we're what we're doing is trying to roll out to the company or risk quantification going away from the standard high, low risk heat maps that you normally see. So it's a way to actually quantify dollar amounts to risks within a company. So you can actually say, you know, we will lose eighty thousand dollars in a year if such risk scenario were to take place. So it was pretty neat. I do have a cybersecurity background and also I respect my audit background with controls really helped as well. So I took a formal course and then studied on the side, found a website with flash cards and flash cards. And yeah, it was. It is a good experience.

Harpreet: [00:03:37] That's awesome. Well, are you going to be writing about it, blogging about it, posting on on LinkedIn, or have you already posted on LinkedIn about it? And by the way, sorry, if my mic sounds distorted, I'm not sure what is going on with this. Maybe who knows? Maybe I'll get myself a microphone for Christmas. I think I might do that.

Speaker2: [00:03:55] Yeah, so I did protege phenomenon [00:04:00] where you learn by teaching others, right, so along the way, while I was studying, I was posting about different topics that I was currently learning and that also helped me throughout that whole process as well.

Harpreet: [00:04:17] Method that's I like that because by teaching something, you get an opportunity to learn it twice, right? So that's kind of like the question on there. Awesome. That's that's awesome to hear. I like that style of teaching. Antonio. Yeah, Antonio, how's it going, man?

Speaker3: [00:04:33] What's up? So Crystal.

Harpreet: [00:04:37] Yeah. Thanks, man. Yeah. How's the first Christmas with with the new baby?

Speaker3: [00:04:43] We took him to see Santa. He was sleeping throughout. He woke up, took a picture with Santa, went back to sleep.

Harpreet: [00:04:48] Like nice right now. Well, thanks for thanks for being here. I know Antonio is making big moves this year too. Obviously big move. You know, being a dad and then moving up to Google. And I think, Monica, you learn something new. A lot of you guys doing big things, but it's awesome to see. So look, if you guys got questions, comments, anything you guys want to share. Any predictions for next year? Anything you just want to talk about reflecting back over the last 12 months or so? Let me know. We'll wrap it up early today, though, so probably just another 20 minutes or so, but still just wanted to hang out with you all four for one last time before the break.

Speaker3: [00:05:26] I have a question. Oh my quick question. I don't know if it's going to help anybody else, but how do you join office hours on a shortcut? I have to go back to all the emails from you where I confirmed for office hours and click on that link. Is there an easy zoom way where I can like bookmark this?

Harpreet: [00:05:47] Did I show up

Speaker4: [00:05:48] On set that link, Antonio? It's just paste, paste a link somewhere into like a word document and put it on your desktop or a note or something. As long as the URL the hyperlink works, [00:06:00] then you can go to that without having to open up the email.

Speaker3: [00:06:04] Awesome.

Harpreet: [00:06:04] Thank you. I got I got a thing about the the user experience for getting on to one of these things. I think I need to sign up for it myself on a on on, you know, the participant end and see what that flows like. So it doesn't show up on your calendar at all. There's not like a calendar.

Speaker3: [00:06:23] Oh, I don't use a calendar. I guess that's why. Ok, but maybe, maybe I should start.

Harpreet: [00:06:28] Yeah. Yeah, that's that's how I get here. Well, actually, no, I just have it on my Zoom account. Matt, you're saying something? Go for it.

Speaker4: [00:06:39] I think I said I agree. But Tony and I mentioned something the exact same time was a quick one also. I just wanted to follow up on what you said about the learning and learning from the protegee method. It's like learning something enough to do it yourself is great. Learning it enough to teach someone else to do it is a completely different thing. If you only learn it to learn how to do it yourself, you won't be able to teach it so well. Learning how to teach is another skill completely in and of itself.

Harpreet: [00:07:12] That's getting better, they're learning how to teach. That's actually, yeah, it's true. Like being able to teach something is itself definitely a good skill to have. Ben Taylor in the building Ben has given.

Speaker5: [00:07:24] I'm better than I've ever been. Nice. I hope all of you are doing well.

Harpreet: [00:07:30] Oh good. Yeah, my doing great, doing great. So what makes what makes you feel better than you ever felt before?

Speaker5: [00:07:38] I think life is funny because you have a lot of shit to work on, and that comes from your experience and insecurities and mistakes of your parents, et cetera, et cetera. Like, we all have stuff to work on. And I feel like mentally, I've just reached a new stage in my life where I feel like I've fixed like ninety nine percent of the stuff in my head [00:08:00] that I need to fix. And that is so nice for me because I can really focus on people around me, people I work with, but also when it comes to navigating politics, sales priorities and work. I guess the last thing to share is sometimes we we talk about imposter syndrome. You're always going to have cracks in your armor, right? It doesn't matter how accomplished you are in your career, you will always have some cracks. And what I mean by some cracks is there is someone you know, that can say something that can make you that can get through your cracks. So think of like a parent or a coworker or someone who you value their opinion if they call you a dumb ass or if they say something. It can make you can get through. I feel like I'm I reached a new level where I have no cracks. And for me, that's really powerful I can run into, I could walk into a room with 100 people that love me the most, and they could all come and call me in Damascus, and that would not shake me. And I think for me, that's what I need right now. But I don't know, just kind of a not the answer you're expecting.

Harpreet: [00:09:04] No, I absolutely love that because as somebody who has a lot of stuff to iron out man, I'd like to learn how you how you got there because, well, it's it's work, man takes a lot of takes.

Speaker5: [00:09:15] I think failure is scary. And so I think you and I've kind of talked about this too, like some of these projects, like there's a risk of failure like you and you want to work on projects where there's constantly risk of failure. And I think learning to embrace failure. No one wants to fail like you want to fight like hell to not fail. But embracing failure is part of the story. There's something that is kind of beautiful in that, like if you have a catastrophic failure is you get fired. You're not like it doesn't mean you have more self-hate, it doesn't mean you doubt yourself. It's just part of the story. Obviously don't want to fail, but I think I think there's I think sometimes we don't embrace failure. We [00:10:00] were scared of it.

Speaker4: [00:10:02] Oh, yeah, I think that's. I don't think that's right. It's a really powerful thing to say and maybe say embrace the learnings from failure or embrace the opportunities to learn from failure rather than the failure itself. A failure and embrace the opportunities that that failure itself brings is the way I like to look at things.

Speaker5: [00:10:22] And I think you're exactly right that it's failures where we learn the most. So that's what we're going to learn, learn from.

Speaker4: [00:10:31] Yes. One of my common things to say is failure is one of the surest fuels for success because, you know, how how better can you learn what not to do by failing, by doing something? Then you take that off the table. You go in a different direction. You should never repeat the same failure. Under most circumstances, there might be some really weird extenuating circumstances where you can't avoid but repeat the same failure, but normally you move away from that direction. Rear restrategize and improve.

Harpreet: [00:11:05] No, I absolutely love it, actually, I've got this piece out that I'm writing on Medium, I'll give you guys a sneak peek. I haven't yet released it, but that's what I was writing about lessons learned from a lifetime of failure. But actually, I've been sitting on this thing for for about a month, almost just like, I don't know, I just can't get myself to publish, but I think I might do that now after after hearing you talk, Ben. Thank you very much. Gina, what's going on? Shout out to Al Bellamy in the building, Mike Diamond, Eric Simms, also the house. How are you guys doing? Pretty good. Thanks. Awesome. Hey, guys, well, Luke, I'm excited to have all you guys here. Let me know if you guys any questions, any closing words you want to put out into the interwebs for twenty twenty two. How about some exciting predictions? Ben, I don't know if you were here last week. We're kind of touching on it a little bit, but [00:12:00] I'd love to love to see what you have predicted for for let's just say let's keep constrained for deep learning next year. Know what do you have? What do you have?

Speaker5: [00:12:10] Oh, deep learning. I think we're going to see some innovations in the next year that accelerate the load of labeling for humans. So, so you could think of like faster topic finding. And I know we try to circle, we try to reduce the number of images we have to label. Do you have to label ten thousand images, a thousand or ten? And so I'm hoping this next year you're going to see predictions where maybe you label two or five. And so the heavy load of needing all this manual labeling, I think that might go away next year or the next three years,

Harpreet: [00:12:43] Like self-supervised learning type of stuff.

Speaker5: [00:12:45] Yeah, self-supervised learning or even the next level. So it's a self-supervised as you're you're building week models and making them stronger. But can I actually have the weakest model surprised me where I'm delighted.

Harpreet: [00:13:01] A let's let's give some trends from a from some data engineering, analytics, engineering, how about analytics engineering trends for 2020? Let's go to let's go to mark for this one. Mark, what do you see for like, what's what's your prediction or forecast for analytics engineering in 2022? What are you going to see? What do you see happening for that, for that space?

Speaker6: [00:13:21] I'm like just diving into that space to learn a lot about it. So I still I don't feel like I'm in a place to say where the trend is going to be. But based on what I'm reading, you know, I think DVT, the Data virtual, I think the recently I think your last year this year, the author for their newsletter to shift it away from data science, to go all in on analytics engineering, which I think that's a really cool signal to to to see that because they're obviously really in tune with the market. And so for them to make that shift and go like, Hey, you know, this [00:14:00] we want to do, of course, is their company. So that's another component of it. But then also, I think some of that's really interesting is, you know, Andrew Andrew, you know, basically it's everyone knows Andrew Coursera

Harpreet: [00:14:15] And Andrew Yang. Yeah, yeah, yeah.

Speaker6: [00:14:17] Andre just completely butchered the last name. Sorry. You know, there's huge emphasis on like, stop making these complex models and just like create great Data and improving your data. And I think analytics engineering really taps directly into that. Like, how can you have software engineering best practices for this later stage of like the Data pipeline that's going to be going to fuel your analytics or your models? So I really think analytics engineers kind of fit nicely within that piece as more people are like less worried about big data and more worried about like quality data coming in.

Harpreet: [00:14:56] Love that man. Super, super insightful, thank you. Thank you very, very much. And Tony, what do you got? What do you got for your predictions for 2022? And then let's go to Russell after that, and Monica doesn't even have to be predictions Data science or whatever, just life in general. And then Eric has a question that we'll get to if anybody knows the answer to Eric's question. Let me know, and I'll have them answer. But yeah, let's go to Antonio Russell and then Monica. Just general predictions for A..

Speaker3: [00:15:24] I predict that Ben is going to do some crazy projects now that he's on another level. That's what I predict. I think

Speaker5: [00:15:31] You're right. And.

Speaker3: [00:15:35] So they let

Speaker5: [00:15:35] The tiger out of the cage excited for next year.

Speaker3: [00:15:39] Yes, sir. But from my perspective, I think I don't know if this is predictions or trends that I'm seeing. I think in a few different industries, it's been already happening. But with like privacy being a major focal point and like third party cookies going away, [00:16:00] I've noticed a couple of different companies now that I've been in and just around the industry is like, what the heck are we going to do? And that shift focus from third party to first party data? So that's that's going to be interesting how how that plays out, because a lot of the world right now relies on third party cookies. And obviously, you see consumers care about the privacy. I don't know if it was like Facebook or Apple when you have to opt in into like them collecting your data. It was like 15 percent or people opt it, in which I was surprised, honestly, because I don't care. I'm like, All right, I know what it's like when you don't have good data, so I'll just let you collect my data just and I don't mind seeing personalized ads. You know, I'd rather see something that I've searched. It actually helps me sometimes. But 15 percent is a very low number. So I think that's going to to effect a lot of different industries, that whole privacy initiative, and I think a lot of companies are going to be working on that.

Harpreet: [00:17:07] Russell, how about you?

Speaker4: [00:17:10] Yeah, I'd like to build on Mark's comment about Data engineering, data science, data analytics, because I've always been curious about the differentiation between those titles because in my mind, at least in any good scientists, needs to be able to engineer, need to be able to analyze. And he could engineer, needs to know better science and a bit of analytics and vice. But if you if you boil it right down to the basics, you know, in my mind, at least a scientist works out why things work and engineer works out how to make them work, and an analyst works out what they do when they're working. Okay, so if you want, if you lump up data to that, it doesn't quite work for the definitions of the title you've got in the data community. There are a bit more nuanced than that, but hopefully next [00:18:00] year there's going to be far less. Concentration on defining what those are and saying, someone is definitely a data scientist or a data engineer or a data analyst and general, there was a great great word for it augmented analytics. I think Cindy Harrison was talking about this recently. I think that's a great for this entire field of Data should just work towards augmented analytics, and I'd like to see that happen next year. One additional thing touching back onto last week's conversation is will there be a future for supersede GPT three? Can't even speak GPT four better than GPT three. It might be interesting to get Ben's comment on that. Yeah, and that's from.

Harpreet: [00:18:54] Awesome, thank you very, very much. You know what? Let's go ahead and let's do Monica's prediction. And then actually, guys, I have actually got to wrap it up because I've got to head to the to the stadium, so my apologies for making it a short one. But let's hear Monica's prediction, and then I'll go ahead and and wrap this up, Monica. Go for it.

Speaker2: [00:19:13] All right. I don't think I have any predictions per say, but more of like hopes and dreams where I'm hoping to see like data quality and data literacy kind of grow more outside of the data professionals so that, like things like self-service, bi can be more used versus just creating a dashboard and then nobody uses it. So really beefing up that data literacy so people can use that data and the data quality aspect of getting away from the whole garbage in, garbage out.

Harpreet: [00:19:49] Monica, thank you very, very much. So, guys, let's go ahead and bat, let's wrap this officers up. Sorry to cut it short. I just wanted to see you guys one last time for the year. We'll be back in action on [00:20:00] January the 7th, the first Friday in January, taking a pause on releasing new episodes until then as well. So that's why there wasn't one released today, and there won't be one for the next couple of weeks, y'all. Happy holidays! Happy Christmas. Happy New Year. All that stuff. Thank you guys so much for being here week in, week out over the last year. Thank you so much for celebrating some big milestones with me this year. 100th episode and 200th episode all in one year and one year anniversary and 100000 downloads all one year. Bam could not have done it without you, and not even a single Friday missed for these happy hour sessions. That that I can recall if I was wrong, then I apologized. But if there is some missed, it wasn't any. So thank you guys so much for being here. Thank you for being a wonderful part of the community. Love you guys very, very much. And hopefully one of these days can come and hang out with all of you guys.

Harpreet: [00:20:49] Take care. Y'all have a good rest of the year. Have a good holiday season. I'll see you guys shortly. Oh, there are a couple of things, though. Tomorrow going live at 10 a.m. with Jeremy Adamson, we're talking about minding the machines his book. I'm also going live on a the twenty first, actually. Yeah, she probably shot this out doing live stream with somebody who was like, That's going to be a fanboy moment for me. I'll be interviewing Akira the Dawn on my podcast. So if you guys know that you know, care of the Don is like, that's the only music I listen to, his stuff is just amazing. So total fanboy moment for me. Tune in to that. They'll be live streamed. I can't believe it. So shout out to the curious line himself, Andrew Berry. He kind of set us up with an introduction. So if you didn't, if you guys want to hear more of me, you can tune in to Andrew Berry's podcast. How did you learn that that episode was released today as well? Those are the other announcements. That's it, y'all. Thank you so much. Happy New Year! Remember my friends, you got one life on this planet. Why not? I do some big cheers, everyone.