The Data Stack Show - 207: Why Niche Data Tools Fail, Broken Hiring Processes, and the GUI vs. Command Line Showdown with The Cynical Data Guy

Episode Date: September 18, 2024

Highlights from this week’s conversation include:Welcome to another episode of the Cynical Data Guys (0:24)Post on Short Sellers in Data (1:36)Investment Areas in Data (4:04)Teaching Git with GUI (9:00)Understanding Data Scientist Roles (12:25)Interview Process Critique (15:39)Hiring Process Challenges (19:19)Defining Team Fit (21:05)Effective Hiring Framework (23:05)Cynical Take on Trust Issues (25:02)Final Thoughts and Takeaways (26:05)The Data Stack Show is a weekly podcast powered by RudderStack, the CDP for developers. Each week we’ll talk to data engineers, analysts, and data scientists about their experience around building and maintaining data infrastructure, delivering data and data products, and driving better outcomes across their businesses with data.RudderStack helps businesses make the most out of their customer data while ensuring data privacy and security. To learn more about RudderStack visit rudderstack.com.

Hi, I'm Eric Dotz. And I'm John Wessel. Welcome to the Data Stack Show. The Data Stack Show is a podcast where we talk about the technical, business, and human challenges involved in data work. Join our casual conversations with innovators and data professionals to learn about new data technologies and how data teams are run at top companies. Welcome back to the Data Stack Show. This is one of our favorite times of the month. It's where we get to sit down with Matt Keller-Herdgibson,

the cynical data guy, and hear his perspectives that have been shaped through over a decade of time spent deep in the bowels of enterprise data in corporate America. Matt, welcome back as always. Thank you. I'm glad to be here for my monthly Festivus. I've had a lot of problem with you people. You're going to hear about it. Cannot wait. All right. Well, one of the hashtags in this first post is hot takes. So I think we're going to start out with a bang here. For those of you listening to a Cynical Data Guy episode for the first time, we have Matt on the show. John and I go through LinkedIn and we pick out posts that we think would rile the Cynical Data Guy up and we do lightning rounds. John's company is

called the Agreeable Data Guy. So my goal is to pit them against each other and get differing opinions and today actually i have four posts so if we can wrap the first three up we can do a lightning bonus round yes bonus bonus round okay round one ding ding okay this post is we're actually actually gonna name the author of this post, Evan Wimpy. He was on the show, amazing episode. Go back and listen to it. He's from Elder Data. And this is a great topic. I actually am so excited about both of your responses. Okay, I'll read it quickly here.

Are there any short sellers on LinkedIn? My feed is peppered with folks pushing their preferred tool or service, sometimes explicitly, sometimes sneakily. I'm as guilty as any. But are there any short sellers or anti-sellers? I'd love to read messages like, don't buy X, here's Y,

with some solid reasoning behind them. Okay, I want some short sells here. Cynical data guy? Anything with AI? No. I would say one that comes to mind is especially since we're starting to get to the consolidation, if your

thing is like, we do this one really thin slice, but we do it really well, I'm short-selling you at this point. Because we're going back. It's like the cycling of bundling and unbundling. We're getting into the bundling stage. We've kind of reached the

absurdity limit of the unbundling. We're getting into the bundling stage. Yep. We've kind of reached the, we've gone to the like absurdity limit of the unbundling. Yeah. And so bundling is going to start happening. So we're like, well, we only do one type of ingestion in this specific way.

It's like, I don't think that's going to work. Agreeable data guy? This is sad for me to say because I think it's a problem but the data quality people have never wanted to spend money on standalone data standalone yeah yeah if you're like we're just gonna sell data quality it's like and my nobody cares my second one which is which has one major exception to it. My second one would be places where there's a really,

or spaces in the data stack where there's really strong open source adoption and one or multiple players that also have been able to make the transition commercialized to bring in there and compete there against those players and not innovate, that's a short-sale. You got to be really innovative. You'd be really good in some unique way if you want to short-sell people that have really large open-source communities

and have already started on the road of capitalizing. You got to not lie to yourself about it. Be more different. No, you have to be 2x, 3x better in order to do that. Yeah, or 10x. Okay, if you could invest in an area right now, what would it be? Obviously, Cynical Data Guy is not investing in Asia.

No. Well, I think you get back to where it's like, what are we in? We're into the bundling stage, right? So I would say there's two ways you could look at that, right? One is I'm going to invest in the people who are likely to be the bundling stage right so i would say there's two ways you could look at that right one is i'm going to invest in the people who are likely to be the bundlers yep or the people i think most likely to get bought by the bum bundlers yeah at a premium yes because the first ones are going to be at a premium and then as we go down yeah yeah that's, yeah. That's right. Yep. I think for me, a little bit different approach, data sharing.

I think FTP is finally on the cusp of getting disrupted. Finally. Finally. So I would say data sharing, two different forms. One, like, corporate data sharing,

like, back and forth between companies. Yep. And then, like, all of the, like, audience sharing, clean room stuff, I think it's going to be.

Yeah, that's going to be huge. Interesting. Okay, we're going to, if we ever start a data stack show fund. Yeah. Right, exactly, exactly. It's going to be full of people saying we're going to change the world

and be going, I don't care. Okay, next post, round two, ding, ding. I've written before that titles are meaningless in data and all that matters is your capabilities. Here's a deeper explanation. I've been a VP with zero reports. I've been a director with 100 data people reporting to me while owning the P&L of a nine-figure data business.

Lower title, quote unquote, but way more actual responsibility. Then there are people who get a senior data title after 12 months of work experience. I know a, quote, senior manager, end quote, who ran data strategy at a greater than $50 billion company after previously leading data strategy at $100 billion plus company, and countless other examples. This is why, in data, anyone competent will calibrate your seniority based on your actual capabilities achievements and impact not based on your title recruiters don't listen to that just send the recruiter this linkedin post say but no my title doesn't matter well but it but we want you to have director level experience and you've only been a senior man.

You're not even getting a call. Here's the thing. So here's how LinkedIn works, right? You buy the LinkedIn recruiter package and then literally you plug in the fields, like certain title range, like that's how it works. Yeah. So I'd love to have a more agreeable take on this,

but that's just how it works. Yeah. I mean, from like a growth standpoint I agree that it doesn't like you know and I've worked at places where they underpaid so they threw around titles like crazy and it's a problem yeah I think

it's also one of those that like when you're hiring it's on you to be to realize this fact and not kind of go the lazy title match route but realistically if I'm talking if you're talking to someone and you're like, oh, don't worry about title. That's usually coming from someone who has like 10 years of experience and has been a VP twice.

And it's, you know, it's like billionaires talking about, you know, money just doesn't really matter. It's like, oh, yeah, I'm sure you feel that now at $50 billion. Yeah. All right. so no agreeable take okay so i think i think the only like potentially positive on this would be it might be worth like as far as like title not mattering it's there are situations where it is worth taking you know getting to work in a better situation, getting to work with better people or a company that's on a better trajectory. We're quote like, cool.

Let's just say like, okay, title doesn't matter. Or maybe a startup. There are situations where I do think this is the right take, but it's not the right take if you're in corporate America and they're telling you like, oh, we're going to give you all this responsibility, but we're not going to change your title your title also because in the bigger companies you could say like well but you know you're getting all this responsibility yeah but you're gonna be pay banned at what your title is yeah right right i do think is it the thing for you individually

and i think it's more once you've had a title yeah then i can go kind of look around like i've been a director i can go look back because i can go back and be a director or something like that. So I think it's one of those that it's like, it depends on where you are and what you've done. But like telling someone that coming right out of school, I'd be like, no, don't listen to that. Titles equate to your pay band. That's why they're important. And in certain companies, they equate to your political prowess and power. So yeah, it's not something to be taken.

It's not important, like it's not going to affect you as a person, but it is something that is in the context of every company and business and you have to take it into account. I agree. Man, that was open and closed. I need to do better on.

Yeah, you got another chance. I have another chance. Ooh, yeah, I forgot. Okay, this is going to be great. Something I'm thinking about as I redo my Using Git and GitHub with R course. I've come to strongly believe in teaching Git using a GUI. Teaching newbies to use Git in the terminal seems like the equivalent of teaching them to use R without an IDE. Teaching them Git with a tool like GitHub Desktop is like teaching them to use R without an IDE. Teaching them Git with a tool like GitHub Desktop

is like teaching them to use R with RStudio. Thoughts? I don't think that's a one-to-one analogy. I think it's inherently limiting, right, to do that. If you just learn it on a GUI, it's going to, yeah, you'll get up and running soon, but it's going to be limiting in the long term. I have less of an issue with doing this in a newbie course than like i don't know where there's you know you're gonna learn how to do it later on because like that's

usually the response when you're like well but you need to learn how to use the command line well yeah but they can learn to do that later how when yeah i don't see that so we end up getting a bunch of people that like you know they don't know they don't know how to go above a certain level because they just they're stuck on these small tools and these guis and stuff like that so for data people i agree i think i agree with the post use the guiI. Well, just use version control, please. Right. Like that would be my number one thing for data people. It is so common. And he's talking about R. So that's kind of leaning toward data science. And they're more like traditional, like computer science, like engineers. So I would say, yes, just use version control. If it's true,

if it's a developer, like, no, like you've got to learn the command line. But for a data person, like, yeah, I can get behind that. Well, it's, and like I said, I will stipulate, if the choices are no version control or use the GUI version control, please people, version control. But I would even say for, I mean, if you think if you're going to be a

data scientist or a data engineer or whatever like we've gotten into this cycle of where like there is you don't go to school really to be a data scientist there is no like there is no function or institution that's going to force you to learn things that are hard and you don't want to learn yeah so it's this amazingly consumer driven market, which then moves everyone towards the, you know, the person has to pick what they want to learn. They have to pay the money for it. So it creates these incentives to make things a little simpler and a lot more accessible, which in and of itself isn't bad, except for then we get all these tool makers who then

turn around and say like, oh, we've built all this stuff so you can deploy notebooks or whatever. And it's like, well, that's not a good pattern to use. Well, but that's all they know how to use. Well, you're just reinforcing the kind of immature patterns of this. We're not unlearning and then moving on to higher things. So you're going to short GUI for version 2? I mean, given our current state, I don't think I would store it, to be honest.

But I just, I don't see where all the incentives are now kind of lined up against it where it's like, hey, how do you mature in your development practices? They're not there. Everything is like pushing you towards

do these things that are, that can work, but aren't great in the long term. I want to take this a little bit different direction. Combining the title thing with this question. Matt, what is a data scientist? Ooh! You know I don't have an answer to that.

It changes so much. I don't completely know at this point, though I believe it has something to do with making a predictive model of something. I mean, this is like a real problem I've been facing. There's been talking with somebody that's trying to hire and they're like, I think I want a data scientist, but I might need a data analyst. But I want them to be like a good data analyst. Yeah.

Like it's a real problem. And like there's this range of like PhD level statistics, machine learning, you know, like, I can build models from scratch. And then there's this, like, I think I've heard the definition before, a data scientist is a data analyst that lives in California. I believe it's a static mission from Silicon Valley. So, yeah, I mean, like, there really are bright people

that, like, are, I mean, nothing wrong with data analysts. It's more of a data analyst-type role. Well well and i think part of that is also like data scientist was originally when it came out it became webmaster it was everything yeah okay sure yeah and then it split off to data engineer and now we've got like the you know like ml engineer and things like that or the bi developer or those things i still don't think it's completely settled down but i also think there's that gap between because data analyst is another one that means this whole wide variety of things data analysts can be like i manually update data in excel and then email it to people yeah sure that could be a data analyst or it can be like I'm doing really

complex analysis and even regressions and some sad stuff that would probably be data science in some places. Or like a decision analyst type of idea. There's a lot of ambiguity. I still haven't figured it out. There's this really great, I guess it turned into

a meme. I have it saved on my computer and Brooks, we should dig it up and put in the show notes. But going back to the titles thing, and you mentioned, you know, Webmaster, there's this great image of Tim Berners-Lee and this guy from AOL. So this is a while back when AOL was peak, right? And they're talking about technology on some talk show you know as guests right these are expert guests and under their titles they had their titles under you know it's like okay you know so and so title right and so this guy from aol also he was you know he had like he was dressed like super provocatively right like he had you know his hair was spiked up and you know

died and whatever. Which is great or whatever. And Tim Berners-Lee just looks like a dad. The title for the AOL guy was like Internet Profit, I think. And Tim Berners-Lee was just Web Developer.

Which is so great. I'll dig it up. I'll see if I can dig it up. The important thing to remember, data scientist does pay more than data analyst. Well, I was going to... Yeah, speaking of titles. Yeah, for sure. That's the thing. Okay. I think we have time for a lightning round. Brooks hasn't messaged me saying land the plane yet. Oh man, this is a good one. Okay. I'm just going to read the interview. I'm going to read this graphic and then I'll read the post. Okay. So the graphic is a good one. Okay. I'm just going to read the interview. I'm going to read this graphic

and then I'll read the post. Okay. So the graphic is a screenshot of a document. The H1 is interview process, and then it's a list of bullet points. So interview process, application review, recruiter screen, hiring manager screen,-Site, Interview 1, Interview 2, Interview 3, Final Technical Interview, References, Offer. And the post is, This many rounds of interviews only tells me that there is no trust between employees and management. The company seems to believe that HR and the hiring manager will fail at their job, so they require three more interviews because the people conducting the first and second interviews will supposedly fail as well. And of course,

you need one more technical interview because apparently the person conducting the third interview is also expected to fail. So first comment, you know, that seems to believe that hr is going to fail i don't trust hr in any of these i have i have never worked i've hired a lot of people i've never worked with an hr that was like oh yeah or you know internal recruiter type that i'm like oh yeah you got this you know what to look for that i want you know know how to, you know, what would be, what's a good fit for this role. We're cool. No, they don't.

Outside of that. I mean, that's really similar to what I used to run. And I would, and I hemmed that down from what a lot of people did. A lot of people try to stick like nine people interviewing in there, but you need to have some sort of process in this. I don't know what they think.

We're going to vibe this and the hiring managers will be like, you seem cool. We're going to vibe this one and be like, yeah, you seem cool. I'd like to have a beer with you. Here's $200,000. We'll see if it works out.

YOLO. Agreeable? Oh, man. I'm still trying to understand the situation here. I guess the complaint, it seems like it's twofold. One, it's too long. And two, there's an assumption here where like the first two steps are done by like hr recruiter group and then like the hiring manager and there's kind of this like pass

off back and forth so first point like it's too long like maybe like if it's too long it's too long by like an interview or two like it's not you're not cutting this in half. Right. It's not seven interviews. Maybe I, but something I have heard, again, talking to people trying to hire right now, is there is way less

patience with candidates with long interview processes for whatever reason. Yeah. Which is interesting. I heard that recently too. A good friend of mine runs product

at a great company and he said, we're, we have to move so fast to get talent, which basically means it's a full-time job because you're running multiple people through a process as fast as you possibly can. Well, I think that's the other part of it is if you're taking three months to go through this process or two months or whatever, that's the problem. Yeah, that's a great point. I can do that in

a week to week and a half right yeah so i mean it's not if it's important and you're doing it you should be moving fast right it's not hr's job like there's a lot of that where they're it's the recruiter's job or whatever like no this is your job to hire yeah the other thing where this gets sloppy is handoffs i do think with with that many steps and the handoffs back and forth, like screen, like recruiter, pass up to the manager, like all those handoffs, if it's not like really clean,

then it will take months to go through that process. And if you're the hiring manager, that's your job to make sure that it's there. I mean, I think there's an assumption a lot of times of like, well, that's HR's role. Like, no, it's your team.

And I think a lot of times when you get the really long ones, part of what you're getting is we don't have a process and we don't actually have like a well-defined framework of what we want from a role. And you see that partially

when they're like, you know, the job description is really generic or whatever. And there's, I don't really know what I want. So I'm going to throw more people at it and we're going to get into a room and then we're going to, how did you feel about it? And it's going to be vibes again at that

point right but vibe HR also great name yeah the domain names available we can start company the other thing he mentions like fail a bunch of different times here like

you know I think that's probably not fair. Between the application review, recruiter screen, if all of this happens quickly, that would be my main measure of success here, to be honest. Like you said, are you going to be able to give a recruiter, HR manager, like, hey, here's what I need. I trust you. I'll hire whoever you say. No, nobody would do that.

Almost nobody would do that. A lot of times you're trying to translate hey here are these mindsets or skills that i want to hire for and they're like okay what keywords do i look for yeah yeah sure yeah i don't have keywords for you yeah but hiring managers can be really lazy writing job description which make it really hard to recruit well. Yeah. The best, the best. I've worked with multiple internal recruiters and the best one was actually a coach. They're like, okay, you know what you want. And I'm going to tell you, like, here are all the things you can do. You know, interview to like all. It was like a coach.

Yeah. Like an advisor who was like here's here are different frameworks to run in the process here's like what to look for it was like this is great right it's like an advisor who's helping you like you know well and yeah especially somebody that can coach on the like what makes a good employee things because you like as a manager you have specific technical skills you want maybe even like soft skills but it but like hey i've been doing this a long time like this is the process i use here the things that for me like make a good employee at this company for these reasons you know that i think that can be really helpful and that's like a second level hiring

thing is the idea of a lot of people view it almost like you're building a baseball team right i'm collecting talent yeah they got different positions but they don't interact that much there's a handoff and they're kind of specialized or whatever where the reality is like if you're a small team you're really making a basketball team and it's got to have a high level of like i understand and you and we work together we can you can't just throw people into it to be effective and if you're running a really large team you're running a football team at that point yeah and you got we work together and we can you can't just throw people into it to be effective and if you're running a really large team you're running a football team at that point yeah and you got to really define what does a lineman look like what is a wide receiver yeah like i mean and

they still have to play together yeah and you've got to really work at it to play you got to drill there is no such thing as a well-oiled machine because you don't have to train a new histin how to work with yeah right like it doesn't work that way right yeah yeah um and i'll give and kind of with this i'll also give the kind of my free advice on this because i did a lot of work on because hiring processes suck most of the time if you're going to hire someone to make this all effective it all starts up front with that idea of like what are the three to five things you have to have? Yeah. Because everyone else is going to have a butt. Unless you're Google or one of the big ones,

you're going to get people that have like a well butt. So you need to know those three to five things. You need to hire for the strengths, not for lack of weaknesses. And you need to like really hone in on what those things are. And then when you get into it, it's, you know, you got to remember, we're not collecting talent. It's got to fit in with this team that we have. And what is the role that we need? Not just I need an analyst, I need an engineer, whatever, but like, how do they have

to fit in with the rest of our team? And how are you going to actually evaluate that process? Because that's why you have people on your team interview them. Yeah. And in addition to that, like, who are you as a company where are you at and like is your role scoped well like in like is this a real job right because like especially with like fast growing companies oh we're gonna like hire this new role and they're like we've never had one of those before yeah and nobody spends any time scoping like what are they gonna do how do they fit in with the team yeah and then like a lot of times they completely miss on budget they like want to hire for like 50 percent of market right like market rate so if you do those two things wrong like that that creates train

wrecks because often like you're hiring maybe even for like a director more senior position that you scoped and then you didn't even like scope it well and then you don't have the budget for it like that can end pretty badly so quick story on that. Early in my career, I worked for a company that did not pay well. It didn't pay well. They mostly hired out of school. The VP who had a degree in

journalism, to give you an idea of what we're dealing with, she really wanted to hire people who had Ivy League degrees. We looked at her budget and i remember telling my boss at the time she you know she's like well she wants people from like harvard stanford i'm like based off of what we are paying i don't want that person from harvard or stanford if they're willing to accept that they're in like the bottom of that class right it's like the

doctor who graduates with d's but but they're still, you know. Still a doctor. Yeah, still a doctor. One slightly, since we're still getting no warnings from Brooks, I'm actually, as the show host, going to interject a slightly cynical take on this one. I get what this guy is saying about trust, right?

And it's like, okay, well, if you don't trust, if there's lack of trust between the people who are doing these things, you're just going to add process to try to control for that one. Right. So that's not untrue. But my gut reaction when I saw this was you have never been raked over the coals of your own horrible hiring decision and felt the pain of how much money that cost you. I mean, not even like someone else doing it, just like sitting there and going like, I made my team worse. Yeah.

I have a giant headache. Totally. Or you've never inherited a team before. Yeah, totally. It's like I am working two jobs because this was a just the hire is such a misfit, right? And like, brutal. If you've never gone through the hiring process, like leading it on the other side,

it's really easy to sit there and be critical of it. It's really hard to do in real life. It is really hard. It is. And most people solve that problem by trying to outsource it to the recruiter or HR. Yeah, yeah. Yep.

Okay, well, easy summary, short sell, if it's not open source, always chase the title and use a GUI for Git. So this has been a great one. This has been a great one. Thanks for joining.

We hope you got a couple laughs out of the show today. We'll be back again next month with a cynical data guy. Subscribe if you haven't so you get notified of new episodes, and we'll catch you on the next one. The Data Stack Show is brought to you by Rudderstack, the warehouse-native customer data platform.

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