Hi everybody. Welcome to another Career Foundry event this evening. I know there are a lot of people are joining, so those that are joining in Big Marker drop your name, where you're joining from, and maybe because this is a little bit of talk about mistakes, it's a little bit like a confessional, maybe what mistakes you've done in your career so far. We want this to be as honest and engaging as possible, so do drop any comments that you have in the public chat and any questions that you may have also in the Q&A tab, because at the end we're going to be having a live Q&A where you can ask Alex anything. Let me just introduce myself and Career Foundry briefly before we kick off. I'm William Events and Communications Lead here at Career Foundry. I see one person can't hear anything, so if there are more people that can't hear anything, please do say something. I hope you can hear me. Yes, I'm William Events Communications Lead here. Alex, can you hear me? I can hear you. I don't know if they can hear you. Okay, some people can hear me, some people can hear me. The one thing I would say is that anyone tuning in on Big Market does work best on Google Chrome, so do check that out and keep me posted if you can't hear. As I was saying, I'm William Events and Communications Lead here at Career Foundry and Career Foundry is the online school for your career change into tech and we guide you from complete beginner to job-ready professional in data analytics and help you land your first job in the field, so we're not any old school. Our programs are so flexible that you don't need to quit your day job and we have a dual mentorship model so every student gets a mentor and a tutor and we also have a job guarantee, so if you don't land the job within 180 days after graduation, if you're making a lot of mistakes on the way, you will get a full refund, so that's our job guarantee. Any questions about Career Foundry do book a call in the description below on YouTube or with one of our program advisors on Big Market. But I would just say one thing, we are very, very happy to welcome Alex back to the Career Foundry channel once again and for anybody in the Career Foundry audience, do check out Alex's YouTube channel, Alex the Analyst. There is some fantastic content over there all about data analytics, also specific tools and general advice, so do check out Alex's YouTube channel and I'm going to disappear now. Alex, I think you should take the floor for the confessional. Seven mistakes to avoid in your data analytics job search with Alex. Awesome, thank you and thank you everybody in the chat. I see you guys and I really appreciate the warm welcome and there's so many people from all over. I love seeing where people are from. We have like Slovakia and Egypt and just all over it's awesome. So hey everybody, my name is Alex Freeberg. If you don't know me, I'll go to this next slide real quick. This is me. That is my picture. I am the CEO of Analyst Builder where you can prepare for technical interviews. I also have a Alex analytics consulting company where I work with tech companies and tech startups on a various array of things and I specialize in SQL, Python, cloud applications and some other stuff as well. But that's not interesting. And of course, I'm most well known for my YouTube channel, Alex the Analyst. And of course, I have LinkedIn and Twitter and all that good stuff. So check me out if you're interested. I speak from Nigeria, UK, Mexico, South Africa. I'm just seeing more people come in. London, Argentina. This is awesome. I love all the people from around the world. I have traveled to a lot of these places but I have a lot of places on my bucket list from a lot of people who are on the channel who I get to talk to. You've got to come here. So I'll come to your place one of these days. Now, I'm going to get started in just a second. One thing I want to say though is William and I were talking beforehand. He's like, I like this topic of mistakes because like he said, it's kind of like a confessional. And for me, it's kind of like therapeutic because I get to reminisce about some of my early days of trying to become a data analyst. And they were very, very, very challenging. And I made all the mistakes you're about to see are, they come from personal experience. It's Alex made all these mistakes at one point in his career. And I don't want you to make those mistakes as well. And that's really all it is. And so a lot of these I have a lot of personal stories with. And so I'll try to share those as we go along. But these are all really, really, really relevant things that you need to take into consideration when you are applying for jobs when you're trying to land a job, even if you already have experience, even if you have a years experience, two years, three years, these things are still really relevant. It's not just for people who are just starting out, although some of these might be more geared towards them. But of course, we'll talk about that as we go along. My wife is texting me, I'm going to turn this off real quick. I told her I was going into, I think she's just saying good luck. Love you. Don't get mad at me. So we're going to go on. I think I have seven of these. And the first one, and I think, and this is no, there's no order to these, it's not, this is the most important one. But this is the first one that when I was writing this out, I was thinking, I was like, one of the bigger things that I messed up when I first started was I tried to do it all by myself. I had no network, I didn't know how to build a network. I didn't really understand what it meant when people said networking. I was like, is that like a networking event where you'd go in person and there's like, you know, not a stadium, but like this area where you'd go and talk to people, like I just didn't understand it. I don't come from that world where networking is like a real thing. And so the first thing I would say is that networking helps you discover job opportunities that are not publicly advertised. What I mean by that is I've had a lot of people, even when I was about like a year or two in when I started actually networking, reaching out to people, joining groups, communities online, and talking with people and engaging, where they were like, hey, you know, we've talked a lot and we have a position open at our company.  And whoever was interesting could like send in their resume. And I got a few interviews that way. And it just networking and not just in those little groups, but one-to-one is a really good way. For example, I help, I'm a part of that network, right? So like if you message me on LinkedIn, we start talking and I probably talked to probably tens of thousands of people at this point. But there are some people who, you know, they'll message me every so often and they'll maintain that relationship. And when something comes along, I passed it along to people. And they really appreciate that. And that is that part of that networking. And I'm just one person, but you can do that with 10 people, 20 people that, you know, you really want to or you're really interested in or that's a, they're at a company that you really like and start trying to build that relationship. So if something does come along, then you're one of those people that they think of. This doesn't always have to be online either, right? If you're in a city, like I used to live in Charlotte, North Carolina, I used to live in Dallas, Texas, both big metropolitan areas. In Dallas, I was able to do that where I networked with people in person, only after I knew what networking was, where I actually went to some meetups and talked to people. But you can do that if you're in a place where there are these types of meetups and you can go and meet people and you can, you know, go in person to places and talk to them. This is the kind of networking that really leads to those long-term relationships. It may not pay off in the first three months of you doing it, but maybe after six months or a year, you know, you're building relationships that are going to last a long time. The next point that I said is that it allows you to showcase your skills and receive validation from industry professionals. So oftentimes when you are, you know, at the very beginning especially, is you don't really know what your skill level is, right? You're applying, but you're like, am I a beginner? Am I intermediate? Should I be applying for entry-level roles? You don't really know. And so networking allows you to kind of share, here's who I am, you know, what do you do, get to know them, start building that relationship. And they can be candid with you and say, hey, look, you know, here's where you're at with this skill. And if you want to be in this industry or this type of company, here's what you, where you need to get. And that they can kind of just mentor you even a little bit, just say, hey, you know, I would suggest you learn this. That's again, networking, because then you can go and learn that skill, come back to them and say, hey, I really appreciate that. And they're like, hey, we're looking for someone who knows that skill will bring you on. And that has happened a lot to a lot of people. And then the last one, and that's exactly what I was just talking about, which is building a professional network, lead to mentorship, career advice, future job prospects. These are all things that happen within a network. And I had zero of these things when I first started out. If I was starting from ground zero today, and I knew nobody, nobody knew me, I would probably start with reaching out to people online, people who I really liked, either on LinkedIn or Twitter, just try to start a conversation with them and say, hey, I'm just beginning. I really like what you're doing and the content you put out. I love to just talk a little bit. And I get messages like that. I probably got 10 this morning. And I messaged all 10 of them back this morning as part of my routine. I like doing that. And so there's other people like me who like replying to people and helping people. And so just find that person. Let's go on to the next one. And this one I'm the king of. And I still, all right, this is one of those do as I say not as I do, because I still kind of have generic-ish resumes, because again, I'm in a different place now in my career where I can be a little bit more generic. People will look me up and they know who I am. So it's a little different, right? So I don't customize my resume for every job. I do wish though, years ago that I had really, I really do wish I had done this. I think I would have gotten a lot more interviews. And it just would have been a lot helpful in the job process. And I just didn't do it. So what am I trying to say? What this is essentially is it's a generic resume where you're not really highlighting specific skills for the position that you're applying to. So for example, I just had one resume that I would blast into any job that was related, marketing analyst, financial analyst, business analyst, data analyst. I was even applying for data science positions at one point or data engineering when I was like thinking about doing that. It was just all the same resume. That's, it doesn't make much sense, right? Because every position is a little bit different. If I was applying for a marketing position, I would want to showcase how my skills are relevant to a marketing analyst position. And this is just high level, right? So like just position based. So marketing versus a data analyst versus a business analyst, you want to cater towards what are these things actually doing in their jobs and then cater your skills and your experience to that job. Now, that's really high level. Even more in depth of that is if you're applying for a very specific company, for example, if you're applying to Amazon or you're applying to Microsoft or applying to Joe's Healthcare Analytics Company or the Alex Analytics Consulting Company, whatever you're applying to, if you look into that company even a little bit, look at the job description, you can then cater your resume to that job description. Now, that takes a little bit more time. It does, it's going to take more time, it's a bigger investment, but you are going to fit that job description better every single time. So me tossing out my resume, maybe I was a good fit for 75% of them or actually, that's ridiculous. Maybe I'm a good fit for 30% of them, right? But if you customize them, it'll take longer, but now you're a fit for 50% or 60%. So you're increasing your chances of getting an interview and that's all your resumes for. Well, 95% of what your resumes for is to get into an in-person interview, right? To get a call, to talk to a hiring manager, that's what your resumes for. So I really do recommend, especially if there's a certain domain. For me, I was in healthcare analytics, because so my resume was healthcare focused. I had healthcare on my job description. I had healthcare experience. And so when I was applying to other companies like bank companies, they're like, this guy's a healthcare data analyst, like why is he applying to this? I guarantee you they were thinking about that. If I had changed it to make it more relevant to financial analytics or banking, then it probably would have done a lot better. And there was a time I tried to switch. I wanted to work at like a big bank like USAA and another place. And I just, that wasn't, it wasn't working. Now, actually, one small story, I forgot to tell on this previous one, I used to work with someone at my healthcare company. And this, it reminded me because I was talking about the banking. He, we worked together for like two years sat next to him for two years, great guy. He went and worked at, I think it was USAA. Yeah. And so he worked there. And after about a year, he messaged me saying, Hey, Alex, we have this BI developer position open. I think you'd be a perfect fit. You'd be on my team. And he was older than me.  And it just wasn't where I was at in my career at the time. But he was thinking about me because he really liked me as a person. And that was that networking piece where I got to know him. And when a spot opened up, he was like, that's who I want to work with. So just a small bit of networking. But I've had that happen now many times over my career where previous people I've worked with or talked with have reached out saying, Hey, Alex, we'd love to have you, you know, join as this position as a data analyst or a data scientist or data engineer.  Then the generic, or the resumes become less important, it becomes more important about networking. Let's go to the next one. I know online presence. Now, this one is, I would say slightly controversial. You don't need an online presence. And you really, I had zero online presence, like absolutely none. I think I had a LinkedIn, but I don't think I'd ever posted on it. And yeah, that's, I just, I had nothing. And so you don't need this, but this is something I do recommend. Because even smaller, I don't even want to call them creators. I would consider myself a content creator, right? That's part of my job now. I do a lot of consulting, but I'm also, I do YouTube. So I have that a bigger brand, but I even see a lot of people who just have 500, 600, 700 connections who are really able to post just interesting things that people really like. And because of that, they get people reaching out to them. And so not only that, there's some other things I want to mention as well. But the first thing is that when you apply to a job, let's say you, your resume gets through, you didn't have a generic resume like me, you made a really good resume, it was cared to a job. The hiring manager is like, okay, we got it down to these five people. Let me look them up online. I can almost guarantee you that you're going to do that. And what ends up happening is, is the people who have a good online presence, they just create a better first impression, or they may even say, this person, you know, they have a bad online presence. We don't want them. If you have nothing, it's kind of neutral, right? You don't have one that's okay. We'll still bring in for an interview. But a good online presence can really help you get that initial interview, or can help you have a good impression when you go in for those interviews, or even have something to talk about.  Not out of the realm of possibilities. The next thing is, is a strong online presence can establish your professional brand and reputation. Now this takes a long time. This is not something that happens overnight. But if you're interested, if that's something that you're interested in, just posting about like your experience in getting a job, or experience in your work, or wherever you're at, just posting about these things, things that are, you know, could be helpful to others, or others could really resonate with, then I really, I think you should do it.  But there's so much content that you can talk about, just about work, and about work-life balance, and all sorts of things. And I personally find it, you know, really, really therapeutic and fun. So you don't have to. This is not a have to do. This is more of a, if you're interested in doing this, I do highly recommend it. It has been, it's not just speaking personally. This has been one that so many people I've talked to, they're like, yeah, this helped me land a job, this helped me, you know, in my first interview, and it really does help. And then the last one says, social media and professional networking sites can help you connect with potential employers and peers. Now, say you have no LinkedIn account, you don't, you didn't even make one. It's not even blank. It doesn't even have your name. Well, you're going to have to go and apply to places, just like everybody else. So you're going to have to go on to Glassdoor, you're going to have to go into ZipRecruiter. You're going to have to go on to monster.com or monsters.com or whatever that one is. Places like LinkedIn are one of the most powerful places to get a job because they do a lot of the work for you. And you can set up your profile and say you're open to work and specify the kinds of jobs you're open to, to where recruiters and people can reach out to you. I have gotten many jobs this way. This is actually how I got my very first, my very first day in analyst job and my second day in analyst job. I got both of them reach out to me on LinkedIn. I just got lucky, right? And that's part of it. It's just putting yourself out there in the best way to give you the best chance of landing an interview. And so this is one that, yeah, I really think is a good one. If you're interested, I'm not pushing it. I really am not. All right, this next one. This was, this is a really interesting one for me because I pseudo did this without knowing what it was before it was cool. Before I started, you know, making my videos on it and now it's, you know, kind of mainstream. I'm patting myself. I'm just kidding. That wasn't me. But you know, a lot of people have been recommending this for a long time and I didn't know what this was. And so what I did was I had my resume, my generic resume, and alongside it on a whole separate sheet of paper, I put SQL scripts that I had written. That's all I knew at that time. All I knew was SQL. And so I had SQL doing a little bit of data cleaning, a little exploratory data analysis, some, you know, simple, not crazy tough stuff, but it was on there. I had like seven or eight SQL code on there. And I would send that with my resume. And my logic behind it is actually really sound. My logic behind it was, well, I have SQL on my resume, but how do they know that I'm actually good at SQL, right? They have SQL on their job description. I know they want someone who's good at SQL. I know, I feel like I know SQL pretty well. Let me put it on a separate sheet on my resume and send it in. Well, that ended up being something that they really liked and we actually talked about in the interview and they were like, yep, these are the types of things that we want to see. What I didn't know is that was actually called a portfolio or a project, depending on how you want to look at it. And I just, I didn't think about it. And looking back, I really wish I had actually created a real portfolio and real projects, and probably would have done even better. But I at least had something, right? I had something to showcase that I actually knew this skill. And that's what these are for. So the first thing says it shows potential employers tangible skills that you have and helps you verify that skill. So for example, I go and I see John Doe's resume. And I'm like, this is a good resume. It looks solid. It has some of the skills that we're looking for. But how do I know he's really good at this skill? It's really hard to tell. Sometimes you can tell him the job description if they talk about it a little bit. But if I can see it, it'd be even better. And then, oh, in the top right, he has a link. And so I go and I click on the link. That's his portfolio. It's a portfolio website. Excuse me. Now, on this portfolio website, he has multiple projects. This project, SQL data cleaning or, you know, SQL data exploration. And I click on it and I see the code that he's written. And he has comments and it looks really good.  He's at least at like an intermediate level. That's what we're looking for. That'll give me more confidence to bring him in for an interview. And I was a hiring manager for a year, but then even before that, I was on a hiring team for two years. So I've been on the hiring process for many years. And honestly, it's not a surefire thing to get you an interview, but it definitely sets you apart. And I can kind of then, when you come in for that interview, I usually will reference, I said, hey, we took a look at your portfolio. We saw these projects, you know, talk about that a little bit. It gives the candidate or you an opportunity to then talk about these projects, how you built them, where you got the data, you know, what kind of insights did you find, what, you know, things within that tool did you use. And so I can't recommend it enough. I genuinely, looking back, have kicked myself many times. I'm like, how do I not know to do this like six years ago when I was, or seven years ago when I was, you know, in those early years of being a data analyst, I only started doing that maybe two or three years after I became a data analyst. It took me too long. Do this now. This is not one that you don't have to do it. But again, this one I really strongly recommend. I strongly, strongly recommend. The next reason for a portfolio project is my second bullet point says it gives you something to point towards during interviews to demonstrate your skills. I, in the first year of applying for a data analyst position, I had a lot of interviews and I'd get in my interview and they'd say, it says, you know, sequel says, you know, Excel. And I think on there I had like a little Python or something and they're like, explain, talk, talk to us about how, you know, how you use these skills. I would kind of go in a roundabout way. Well, you know, I know how to use joins. I know how to use group bind for aggregate functions and, and let me tell you something, that doesn't sound good in an interview. I've heard a lot of people say that in interviews. It doesn't sound good. You're just saying what sequel does. It's like, you want to talk about how you use sequel to, you know, actually do something, how you use it to clean data, how you use it to create automated processes. If you know how to do that, or just how to aggregate data and what you can find from that, right? It's about solving business problems, use tools to solve problems. And so projects are you're completed. Here's where I took the data. Here's what I did with it. And here's what I got from it. And so you can take it and you can talk about it in an interview and say, Hey, I built this, I took this data. I did these things in sequel. And here's what I got out of it. And here's what I was able to do with the data. And that speaks so much better to you as an employee, because you've really worked hard on, you know, working on the skill, building something. And you can point to that in an interview sounds so much better. All right. Number five. This is a mistake that I made one time. It only took me one time to realize this. And I'll tell you the story before I even get into it. I was applying for my first data analyst position. I just was looking for any job. And this is, this is something that doesn't happen all the time. But what ended up happening was is that they reached out for a data science position. I didn't fully know what that was. But the pay was like 80 grand. And at the time I was making like $36,000. So, and I was living in Dallas. So, that's like really low for Dallas. And I was like, I would take anything. I'll take any position, anything. I just want experience. So, I went in for the interview and again, I don't know why they were interviewing me. I just got lucky or whatever. Well, I thought I was getting lucky. So, I got in there and I started asking questions about work-life balance and about being in person versus, you know, how often do I need to be in person? Because again, I didn't, I would have done it either way. I was just curious, asking about culture and all these things. And I didn't really even fully understand what the business did. But I started asking more questions like, what does this come, what do you guys do? And they're like, well, here's what we do. It was a payday lender. I was like, quick loans or something. I don't remember. And I started to find out more about it. I'm like, this is a really sketchy business. Like it just sounds like you're loaning money to kind of broke people and you're kind of like making a profit off of people who can't afford things. I was like, that's really sketchy. Then I started asking more questions about like company culture and all these things.  It's great.  There was just a big red flag somewhere in there. I went back home and I looked them up online and it had a 1.5 rating out of five stars on Glassdoor, on LinkedIn, on all these places. It was horrible. All the reviews said, never, ever, ever, ever, ever work there. It is the worst place to work in the world. Like thousands of reviews. That was like my wake up calls. Like, I need to research these places first. That was one of the first few interviews that I took trying to become a data analyst. Really bad. Really bad. It left a bad taste in my mouth. I was like, I need to look these companies up before because I have morals. I have a moral compass that I would like to maintain throughout my career. And so I don't want that to happen to you. Now, some other things that it's really beneficial for. And these are the ones, and that was just like an anecdotal story of why, partly why. But these ones are really, really important. The first thing is that it helps you understand the company's data and how they operate. So for example, I worked with healthcare analytics for many years and I did IT analytics as well, cybersecurity, operational analytics, all these things. And what I've learned is that you can tell, and maybe this comes with a little bit of experience, I can't, it's hard to put myself in my brain when I was first zoning out. But I can look at a website, I can look at a company, I can look on their website, and I can tell pretty quickly what kind of data they use. I can tell pretty quickly what their business model is, what they're trying to do with their data. And when I go into an interview, I can then talk about that. I can say, you know, I was researching your company, and it looks like this is kind of what you're doing with your data. Is that accurate? And they'll tell you, oh, we're actually doing this. That gets a good conversation rolling for, oh, well, you know, that's a really interesting process. Have you guys thought about doing something like this? Or have you guys done this before? And that definitely comes with experience, right, just knowledge of working in these systems.  I don't want to look like a buffoon when I'm in this interview. They're like, I'm like, Hey, what do you guys do? They're like, come on, guy, like, at least look up the company, know what our company does, show a little bit of passion, a little bit interest. The next one says you can tailor your responses based off of their business or part of the business. That's kind of what I was mentioning earlier is, they'll ask you a question.  Because again, you're interviewing for a position at that company. They want to make sure you're a good fit. So if they ask you a question about that, you can say, well, I don't know much about, you know, claims data, right, in healthcare. That's something that I know about. I don't know much about claims data, but I've really been looking into it. It sounds like it's a really important part of the payment system for, you know, healthcare and how that works. And you just looking that up and showing some initiative, even if you don't know what it is, just showing that initiative looks really good. It's like, okay, this person is really interested and cares about this. And the last thing is it'll give you great questions to ask at the end of the interview. Now, not a lot of people talk about that. It's usually like how to answer the questions, but good questions at the end of an interview. Beautiful. I love them. I've had some great, I've been interviewing people where they've asked me some great questions and it's left me thinking. I'm just like, they leave and I'm there with, you know, I remember I was, oh, geez, I'm forgetting your name, but it was an old colleague of mine. We would do the interviews together. I would just sit there. I was like, that was a really good question. It like made me think of them and it kept them in my head. And there was one person who was a business analyst on our team who we hired, not because of that, but that really, I remember I was like, this guy had really good questions and it just, it's really good. It shows some initiative, some thought. And so if you research the company, you can use that to be like, I saw on your website or I saw as your company does this, how do you guys get the data for that? Or what systems do you use to collect that data and, you know, what processes do you use? I'm just pulling this out the top of my head. But these are questions that you can form before you go into the interview. These are things that you need to do. I'm going to check time and grab some water real quick. Oh boy, it's 1130 already. I'm running long. These personal stories always get me. I talked too long about these personal stories. The last one is not working with a recruiter. Now recruiters, if you don't work with a recruiter, you just do it all by yourself. You're going to end up like Wilson here. Now, if you don't know Wilson, look up Wilson Castaway. It's a movie, fantastic film. Highly recommend it. But you're going to be all by yourself.  It's going to be you versus the world. And it's going to be very, very, very, very, very tough, especially in this tech atmosphere and job market that we're in. It's hard to do it by yourself. I cannot stress enough how important recruiters are, especially in today's age. That's how I've gotten almost every job. My first job as a data analyst, recruiter, second job as a data analyst, recruiter, third job as a data analyst. I just got a promotion at my work, so it doesn't really count. But recruiters are crazy important. This one says the wrong thing here. This is from a previous one. Ignore these. I must have accidentally deleted these and left some stuff from the old webinar. Ignore the stuff there. I'm just going to talk about it. Now, recruiters, I'm going to tell you, I think I've told the story before. I worked with my very first recruiter back in 2017. Oh, yes, 2017. When I worked with this recruiter, I thought it was a scam. And in fact, I thought I was going to get like, he asked me to meet in person. And so I go to this building and I'm like, I've never met with a recruiter before, never talked to the recruiting before. So I was really skeptical. I was like, this guy is trying to help me get a job. That doesn't sound right. There's something wrong here. I'm getting scammed. So I tell my wife, hey, I'm meeting with this recruiter at this location. If I don't call you in an hour, something has gone wrong. I was like, I've been mugged. I've been murdered. Or I'm in an interview. I was like, either way, I was like, just call me at this time to make sure I'm okay. It turned out that I got my first job from that interview. It was great. But I was very, very, very skeptical. I didn't understand how they worked. So here's how they work. Recruiters, there's usually two types of recruiters. There's third party recruiters. And then there are company recruiters. Now, third party recruiters are just a standalone recruiting company. That's all they do. They're a recruiting company. And often they're called tech consult consulting recruiters or tech recruiters or just recruiters. And it's exactly what they do is they partner with companies. So I worked with a company called KPN healthcare analytics. And it's on, you can go on my LinkedIn and check them out. So KPN consulted with this company to hire people.  They don't have to go through a thousand resumes. This company would do it all for them. Then when this company got a person, they would bring it to them. They would bring them in for an interview. And once they hire them, they would pay the recruiting company a service fee. Usually it's like 10% of the person's salary. So when I got on salary, I got on salary for $63,000 at that company. So they didn't take my money. They just said, okay, we're hiring them for 63,000. We're going to pay the recruiting company $6,300. Now if they found it in a week, that's $6,300 in a week. So that's how recruiting, those recruiting companies work. And so you're not losing anything, right? You're not losing, you're not going to lose some of your salary. You're not going to do any of that. You're just getting, sorry, I saw somebody in the chat say something about the mugged murdered. But you're not giving up any money. It's essentially a free service to the candidate. The company pays for that service. Then there are company recruiters. Now these recruiters are working basically as a single recruiter or multiple recruiters within a company, and they work for KPN, for example. We didn't have recruiters. We used a third-party company. But for a lot of bigger companies, they'll have a recruiting team where they'll go out and get people. And so how can you work with these recruiters? One of the best ways. And I have videos on this. I posted about LinkedIn. So if you want to check it out more in depth, the best way to work with recruiters is to go on LinkedIn. I've gotten two jobs from LinkedIn. Highly, highly, highly recommend it. Set up your profile. Make sure you have your skills and your job description. Put your resume on there. Make a good LinkedIn profile. And then say you're open to work. Hear the jobs you're looking for. Really, really recommend it. The second thing is, is I would reach out to recruiting companies. So I've messaged recruiters at companies. I would message third-party recruiting companies, send my resume. And then I would try to partner with them. There was a point back in 2018 when I was trying to get my next day down this job. I was working with seven different recruiting services or people. So I was just, and I was just constantly, once a week, not constantly, but every week I'd check in with them and say, hey, have you got anything come across your plate that you think I'd be a good fit for? Like really appreciate your help. And then, you know, one would give me one for that week. And then the other six wouldn't do anything. And so I just keep hounding them essentially. And it was a numbers game. I just, it was as much as I could, as hard as I could, I was just trying to get, you know, a different job for various reasons. Now there is one thing, and I actually saw, I see this in the chat right now because I'm glancing over every so often when I see it. I shouldn't do that, but I am. It says, are they trustworthy? There have been, and there are, fake companies out there that want your information to do that, or to steal it or to sell it or to get you to buy things that you, you know, say you need and then they charge you for it. That happens. That is a real thing. In my experience, that's not crazy common. Like if you work with 20 recruiters, maybe one of them, that would, that would happen with. I don't have the numbers in front of me, but look that up. Make sure you're aware of what to look for. Working with recruiters though, I cannot stress how important it is. It is very, very, very important. So that is a really important one. The next one is focusing only on hard skills. I only had hard skills. Well, at least I thought I did. I only had hard skills at the beginning of my career. I was like, I know sequel. Please hire me. That's it. Sequel is like my bread and butter. That's all I knew. So I really kind of, I really kind of pushed that hard skill. I was like, please, anybody, please hire me. I know sequel. But hard skills are not the end all be all. In fact, I think more than it's like 50-50 once you get into an interview. Hard skills, I believe, get you into the interview. Soft skills plus hard skills, 50-50, get you the actual job. And here's why. When you apply for a job, they're going to look at your resume. Before you come in, at least one person is going to look at your resume and say, hey, he's got the hard skills. They're going to bring you in for that interview. So if you get in for an interview, you at least pass that barrier. You at least know something or enough of the hard skills you have at least have a good enough resume to get into an interview. But once you get into that interview, they're going to be like, okay, we know you have the hard skills. Explain the hard skills. But we're also assessing your personality. We're assessing your interest in this position. We're assessing how much you know about the company, how interested you are. A lot of these other things. And so not just hard skills are important.  These things really matter because I've had a lot of people on paper look great on resumes. Then they get in from interview and I'm like, I would never hire that person. I just, that is like the opposite of the person that I want to hire. And I've gone back to like, when I was the hiring manager, I go back to the recruiters and say, hey, don't bring in people like that, like try to vet them for that specific thing or these types of things and their personality or the way that they do things because I would never hire someone like that. So those are really, really important. Soft skills are kind of those intangibles like we're talking about work ethic, communication, time management. These are things that it's hard to put on a resume. Some people do it. I don't. It's hard to put on a resume. You don't just want to say, I'm good at communication because you may not be good at communication. You may just have it on your resume as a soft skill. And so how you actually communicate, how you actually talk to them makes a big, big difference. And like I said at the beginning, hard skills get you the interview, soft skills get you the job. I fully believe that. I think that's the last one. Let me see real quick. So just to summarize before we move on to the Q and A time at the end, which I love, I've seen a lot of great questions. When you're, when you are applying to jobs, let's say right now you have no resume, you have nothing. You're just sitting there. You have zero chance of getting a job. You don't have a LinkedIn profile. You don't have a resume. You know zero skills. You're just, you're somebody.  You have zero chance of getting a job. All of these things that you implement increase your chances. Creating a resume, that's going to increase your chance of getting a job substantially. That's very important, right? Let's say it's 10%. Then you create a profile. It's another 5%. Then you start working with recruiters. That's another 10%. And then you start being, getting better at communication and all these things. Each thing gives you a higher percentage. If you only do two of them, you only do one of them. It gives you a smaller percentage. That's how I've always thought about it. In my mind, I'm like, I need to give myself the best chance I can at getting a job. After that, it's kind of a numbers game. It's a waiting game. It's a numbers game and there are fluctuations in the market. Maybe right now it's not the best hiring. I've looked at a lot of data. I've talked to a lot of people. I think 2024 is actually going to be a big year for hiring, especially during the second half. This first half is the beginning of a new year with financials and all these things. It's not typically a very high hiring season. But when you hit over the summer and then you hit towards the end of the year, I actually think we're going to have a big hiring season at that time. Position yourself. Add those percentage points throughout this next upcoming year and start applying. You don't have to wait until the end of next year. Start applying now because then maybe you'll get an interview or you'll get some opportunities. You can start networking. You start building things so that when hiring picks up a lot, you're there to ride that wave instead of just starting and then you're like, oh, no, I can't ride the wave because I don't have anything ready. It's kind of a numbers game. It's a preparation game, but there are still a lot of jobs out there, still a lot out there. You just got to be prepared for them and apply for them. With that being said, I'm going to bring Will back.  And then we'll do some Q&A and I'm going to get us up a water roll. Alex, this is great. Loved it. Absolutely loved it. Also, 2024, big year for hiring. You heard it here first. Thank you for that. And also, I thought Alex researching or not researching before interviews. I thought there was some fantastic advice on that slide. And I think one thing which our career specialists at CareerFoundry would also say is it's a fantastic chance for you to scope the company. So don't feel like all the pressures on you in the interview. It's also your chance to be able to scope the company and see whether you'll be a good fit there or if you even want to work there. So I love the radical candle. That was fantastic. I'm going to jump into the questions that a lot of questions are coming through. I think we'll just pick out a few first, unless you've seen any that you want to hone in on. No, you do much better than I do. You ask the better questions than I find. It's a great question to come through from PE initials. What to do if we've been messaging people on LinkedIn and not getting any responses? It could be, I would say just on a quick, it's probably one of two things. One, your message is probably wrong. And I say that in the most loving way. Just when you message somebody, there are some cultural things or societal things that you shouldn't do. You shouldn't ask for an interview. You shouldn't ask them to immediately review your resume, although you can or look at your resume. You shouldn't immediately ask for something. Typically, you want to introduce yourself and create that relationship first. Hey, I saw you work at this company. I'm really interested in that. I'd love to learn more. I just want to reach out and connect with you. That is a very soft approach. You don't want that really hard firm approach of, I want a job. Your job is a recruiter. Give me a job. That could be the first issue. The second issue could be your profile. If somebody messages me, I often look at their profile just to see what it looks like. I'm just curious. I'm a curious person like anybody else. So if I get a message from a random person, they're probably going to click on your profile. And if it's a bad profile, if you have nothing on there, no posts, no engagements, just a blank profile, I would not be interested in talking with that person, because I don't know them.  So those are the two things I'd look at if that's the issue that you're having. I think that's some great advice. Also on LinkedIn, you see the quick apply button. Never press it. You think that you want to press it. Just don't press it. Just have a little bit of thought and approach with a great question. Take a little bit more time. Another great question coming through. And apologies if I pronounce anyone's names wrong. Nicole is asking, Alex, how many projects should a candidate aim to include in their portfolio? At a minimum, I recommend three. Just three solid projects. They don't have to be crazy advanced. Just something to showcase your skills. You know, on my channel, I have a ton of projects. I think those are good projects to start with. Because you're just looking for the intermediate skills of, let's say, Python of data analysis. So you're looking for someone who knows how to use a pandas data frame and manipulate the data a little bit, maybe bring in the data from a file. Not crazy difficult stuff, but three projects at least shows, hey, they didn't just stop at one. Three is like, hey, they put some time and effort into this. They built a website. This is something they put a lot of time into. I wouldn't go higher than about seven-ish because then it's too many projects. Once you get to seven, then you start taking the bad ones off and you start replacing them with better ones. You just keep doing that until you only have good projects, right? You just seven great projects. That's my recommendation. I've seen people do 10, 15, but that's not my personal recommendation. You might start to get a little bit overwhelming if you're presented with 10 or 15 projects as in a hiring position. I know we've got a lot of beginners watching this evening too. So if a resume does land on your table, Alex, what are the core hard skills that you want to see in terms of tools? Because there's so many tools out there. What are the main ones that you want to see? That's a great question. And actually, this is a good place to mention this. I always talk about SQL, Excel, Python, Tableau, PowerBeyond, my channel always because I think there are such core fundamental skills. But I myself know like 20 other skills that are not those because I just worked with multiple cloud platforms I've worked with in my job. I worked with so many different tools, some proprietary tools and different Microsoft tools that most people haven't heard of. And those are the core skills if you're looking for just like a general data analyst position. But when you look on a job description, you'll see all these random tools, right? It's like, oh, what's Databricks? What's Azure Data Factory? What's AWS Glue? What's Looker? What's all these different tools? I have no idea what those are. Well, those are the tools that that company is using. So when I was a hiring manager, we were, oh, geez, it's escaping me at this moment. We were using this Microsoft tool that I had never used before. My job was to migrate all of our data to Azure cloud. That was what I was hired to be a manager for. So we had this old system and we were migrating it. But I needed to hire people who had this skill, data analysts, business analysts who knew this tool already. And it's a niche tool. It's like not a huge population of people. And so I needed someone who already knew the tool. And so that really narrowed down who I could hire. So I always recommend SQL, Excel, Python, Tableau, Power BI always because look at the percentages. If you apply for a data analyst position today, there's probably about a 75% chance. One of those skills will be on there. I'd say a 30% chance, two of those skills. Well, maybe Excel, SQL, I'm going to be on most of them. But there's going to be a high percentage chance that those skills will be on there. Then there's these small little niche tools or things within tools like within the cloud or within some smaller tools that you can learn. But it gives you a smaller percentage chance. I'm not saying don't learn it. But if you want to give yourself the highest chance, learn those tools. So to get back to the question, when a resume comes across my desk, it depends on what I'm hiring for. When I was on the hiring team for data analysts, we needed somebody who knew SQL really well. And that was our main thing. Python was a plus. And then Excel. So that's what we really were looking for. But it would be a bonus if they already knew Azure because we were starting to migrate to Azure in that position. So I'm looking for things that are relevant to the position we're hiring for. When I was a hiring manager, I didn't care about SQL because we weren't using it. We were trying to migrate to a system where we could utilize SQL, which was in the cloud in Azure, but we didn't use it. So I couldn't hire for that. And I needed someone now who knew this tool. So look at the job description. See what they're hiring for because that's what they're going to look for. They're going to look for those things. What's ever in their job description, they're going to ask about it. That's what they're going to look for. Awesome. Great advice. I also loved how you broke it down into percentages and probability. I wouldn't expect anything less from a data analyst, but I think that was a great approach to do it too. I think Maria has also got a fantastic question. And this is a question for people who are recent graduates. The job market can feel a little bit intimidating, especially when you just graduated. How is the best way to find a job for a recent graduate? That's from Maria. Yeah, recent graduate. That's my blood and butter, right? People who are trying to break into data analytics. Also people who are like out of college, out of their master's program. That's the majority of people who I talk to and who I cater my content towards because that's where I was. The best thing that you can do is everything that we just talked about in this webinar. And I'm being genuine about that. This all is catered.  The biggest things, these are the hierarchy for you. Create a really good resume. There are lots of resources for creating great resumes. I have some myself. Create a really strong resume. Then create a really good LinkedIn profile. Then work with a recruiter. If I could only choose three out of this whole list, I would do those three things. Those are the things I would start with. I would make really good and I would do them relentlessly. I would keep updating my resume as I got more projects, as I did more stuff. I would keep updating my LinkedIn. I create posts. I would then work with a recruiter and not work with one recruiter. I would work with as many recruiters I could possibly work with. I'd email them every single week. I'd call them once a week and I would keep messaging them until they blocked me because that is just unfortunately how you have to get a job these days. It's similar to how when I was when I was first getting my job, it hasn't changed too much. It's just maybe a little bit tougher these days, but genuinely persistence and being really consistent at it, I applied to thousands of jobs. That's an exaggeration. It was like a thousand and ten, but it was over a thousand jobs. I worked with tons of recruiters and it's just that consistency and that persistence that's going to really help you break in and get that first job.  What kept you going through the storm? No. At that time, when I applied to those thousands jobs, it was over a thousand jobs. I was making $36,000 a year. We just found out my wife had gotten pregnant. I was having that, oh my goodness moment, I need to make more money. I went all in. I was like, I am going to make this happen. I don't care how unqualified I am or how little I know, I am going to make it happen. I did. I had that never give up, never quit, don't stop until I make it happen kind of attitude. That's where I was at the time. I think that's awesome, but I think it does go to show, though, that keeping on track, keeping the goal in aim and doing methodically, we also see it the career foundry, the graduates that go through the ones that put in the work and the ones that apply on a regular basis are the ones who are more likely to land that job. The motivation and that will to land the job is also going to put you in a good place. Let's talk transferable skills. David's got a great question. It's a little bit on a specific industry, but I think we can also take it more general. Do you have any tips about highlighting transferable skills when your experience is all in one sector? David is also a healthcare analyst. Cool. Yeah, so I worked. This is great because this was me. I worked as in healthcare for years. I was working in nursing homes. I was working in rehabilitation centers. I was working on the actual healthcare side. Then I was working in ERs or ICUs or different stuff. That's what I did throughout college and then out of college. That's what I did. Now, I didn't have any data analyst experience, but what I did was I was like, okay, this is something I think was really helpful. I'm glad you're asking this because I didn't really, this is kind of like don't have the generic resumes like catering your resume. I did do this one thing, which is I realized that my healthcare experience was really valuable. I was like, okay, I have domain knowledge of how things work in an actual hospital or at a rehabilitation center or at these places. I understand how they collect the data in the EHR systems or however they're collecting it and why that data is important. I understand these things. I just haven't ever used it in the data world. On my resume, I would then write experience collecting or using data like this. I would talk about claims data. I talk about HixPix codes or ICD codes or Loint codes. I would talk about diagnosis codes and how we would use that for billing and all that stuff. I really do think most a lot of jobs you need domain knowledge for, you can use that and talk about it in a way that somebody who's hiring for a data position is going to be like, I recognize that that person knows what they're talking about and that's a good thing. That's a really good thing for a recruiter or a hiring manager to see. I think another thing also working with career foundry graduates and hosting a lot of online events is that we have a lot of people thinking about career change, thinking about shifting over and they come from either like a marketing background, they come from a liberal arts background, so many different backgrounds. When they're making a career change, the first thought is that I'm going to be starting completely at the bottom. I'm starting at zero, but forgetting all of the professional experience that they've had before, that wealth of knowledge, the transferable skills, presentation skills, soft skills, all these things. So actually, you're not starting at the base, you're not starting at nought, you're bringing all that knowledge and they're going to also help you in your new career. Alex, I know that this evening we also spoke a lot about recruiters, finding recruiters. Eboni's got a great question. How do you go about finding recruiters via LinkedIn? I have a video that literally shows you how to do this. I recommend it. I don't remember what it's called. I have a video doing showing this exact thing. I show you how to do it. I'll talk about it, but it might be, you know, this old noodle of mine, I'm not 100% if I'm going to get it all exactly correct, but here's how you can do it. And this is like recruiter goal. What you can do is you can go and what I would do is I would apply for a job. I'd go and I'd say, oh, here's a job for Alex Analytics LLC. That's my company. I found this job. I'm going to apply for the job, and then I'm going to click on it. I'm going to go to the company. You can go down and find people. You can then search for people within that company. I would type in recruiter. Then you can find all the recruiters. You can message them and say, hey, I just applied for this job, and you can link the original job. You can say, I'm really excited about it. I think my skills really fit it. I'd love to chat more about what the position entails. Just something quick, something easy. And I have in that video somewhere, I have some information on that, but it's so easy. And you can do that for any job that you're like really, really, really interested in. If you find a job that you're like, I really want that job. That fits my skills perfectly. It's exactly what I'm looking for. It's in the location I'm looking for. And I've had lots of jobs like that. I never got called back for, but I'm not salty about it. You can go and you can actually find the person or the recruiter for that company. That is lovely. Highly recommend it. The next thing that you can do is you can have recruiters reach out to you. Now, this is on the profile side. You're going to go to profile and you're going to say, give me a second. I'm going to go on my link there real quick. I'm not pulling it up on my profile probably because it's got a lot of stuff on it, but you can say open to, here it is. You can say open to, and then there's finding a new job. And then you can specify exactly what you're looking for. Job title, location, onsite or remote, your start date, full-time, part-time, and if recruiters can see it or if the anyone can see it. So those are all the things you can specify. And I've had over the years, even when I had no experience. I had lots of recruiters reaching out. That's where I was working with all these recruiters. So I highly, highly recommend those two things. Great advice. See LinkedIn as your friend. We're also streaming live on LinkedIn at the moment. So hello to everyone there. I know we've got a question over there, but firstly, it's the time of the evening where we're talking about existential questions. And Jelisa's got a great question, an existential question. Also, Basing, that you said earlier that 2024 is going to be a big year for hiring. Do you think the data analytics role will be around for a long time? And how can it potentially evolve over time? Right. And I'm sure you're referencing AI. And I've been, if nothing else, semi-obsessive over this for the past year. You probably don't see it a lot, but I look into this stuff way more than I should. Probably more than much. Probably, I'm in the 99th percentile for sure. And what's really great about my brand and who I am is I have connections to a lot of really cool people who know more than I do.  And I know director of analytics at some big companies. And I'm like, hey, how is, how do you see this affecting your business or your company? I talk about them. Talk about that with them. Here's what I've distilled over the past year and what I see, how I see the world of analytics changing and what it's going to do in the future. I think I had, I think, did we do a webinar on this in the past? We did one on chat GPT. Yeah, maybe it was just that. Which was a good one. Okay. I couldn't remember if we did a whole webinar on this though, but anyways, I digress. Everything that I've found is AI is great. If you just go on LinkedIn and Twitter and type in AI, all you are going to see is AI is going to replace all the jobs in tech. AI is going to do this. AI is going to do this. It's a lot of hype. And there are some truth to what they're saying with some of the things that the abilities that it can do. I have used AI enough and I've talked to so many people, probably upwards of 30, 40 people who are really experts, some of who are even trying to implement AI into their companies. AI, if nothing else. I haven't heard anybody, let me rephrase that. I've heard one person say, and I'm thinking of a specific person who was just like, it could, but I don't see it happening, but it's possible this could happen. The other 39 people, let's say it was 40, the other 39 people, every single one of them was like, no, this is going to add more work and it's actually going to have to expand our team to accommodate. Now, here's why. Now, when I put myself in the shoes back when I was an analytics manager and I'm like, okay, how would this have impacted my business? I thought about this a lot. AI is really cool, really great stuff, especially for coding, for building things, it's great, but AI is not perfect. In fact, I've used it so much now that I'm like, I really have a great feeling that even if it gets a little bit better, progressively better, it's never going to get to the point where it's going to replace me as a person, just because, just how I use it. Now, if I'm back in that manager position and I'm looking at it, I'm like, how would I integrate AI? Well, I know of few specific things I could integrate AI into, but I can't just put AI into the system and it does everything. It's not possible. It would not have been possible back when I was a manager. I just know it, because how our systems work, how our data are siloed, how our systems are connected, how we collect our data, how we store our data in these cold and hot storages in the cloud, it just would not have been possible to ever replace anybody. But I know there are specific processes within our thing that AI could definitely have helped with. And so I would have brought someone in who knows AI, like an AI engineer or a data engineer who could implement it, to help streamline that process. Once you streamline one, you're going to streamline more and you're going to keep going, that's going to take years of work. Those are just parts, bits of the whole. The whole is where everything is. And so when I talk to all these people, they're like, well, we're trying to implement it for this single use case. We're trying to implement AI for this workflow. But that's only like 1% of the work or 5% of their work. It's very small. So right now, even within the next 10 years, I see AI being an enabler and a grower of what we're able to do and how we're able to do our work. So for analytics, I genuinely don't see it reducing work or the amount of people who are in analytics. I see it increasing it. And almost everybody that I've talked to, almost everybody says the exact same thing. They're like, oh, yeah, we're going to have to hire on more people for this. And it's only for this specific thing. There isn't just a data analyst AI. Even the data analyst AI in Chat UET, I've used it a lot. I never even made a video on it because I am talking about what I experienced. But even when I was using that, I was like, this is good, but it's not great. This is like entry-level stuff. An entry-level analyst could do this and probably do a little bit better, but it helps with the workflow. And so from my experience, my personal experience, data analytics is going to be here for a long time. I do think though that AI is going to become a necessary skill in the next two, three, five years. It's going to be implemented in a lot more places, especially as Google and Microsoft start rolling out co-pilots and all these different AI assistants. You're going to need to know how to use them. But all these core skills are still going to be there. You are still going to need to know how to use SQL. You're still going to need to know how to use Excel and Python and Cloud platforms and Tableau and Power BI. I promise. Come back to this webinar in five years. Now, I am wrong. I will give you a $1,000 cash. I will then mow you that money. If in five years somebody bookmarked this, somebody put a timer, $1,000 cash, I promise you. I am so confident you are going to need to know those skills in five years. It's like 99.9%. But AI is going to be an assistant to that. In the future, Harry said deal. Harry's got me. Message me. I'm not even joking. Somebody put that on their calendar five years from now. In the future, you're going to need to know these skills. These skills aren't going away. Businesses need information. They thrive on data. They thrive on these things. More companies now are going to need data teams that they never had before. Especially small and medium-sized company who have never developed a data team. They're going to have to create a data team to keep up. They're going to have to. Who is going to analyze that data? Are you going to fully rely on AI to do that and not have somebody who really knows what they're talking about? You're not going to do it. I just, it would be such a bad move. It would be a bad business move to do that. I'm going on a rant. I've completely taken over this QA section. I'm very passionate about it. I really am. Because even eight months ago, no, at the beginning of this year, let's say 10, 11 months ago, I went through this existential, I'm like, is analytics gone? I just didn't know enough about it. Now that I've used it, I've talked to tons of people. I follow it really closely. I'm more confident now than ever that analytics is for sure going to be around even 10, 15, 20 years from now. I've seen exactly the same just to echo your points. I think at the beginning of the year, AI has been here a lot longer than just this year. But with the arrival of chat GPT, especially at the start of this year, I think there was a lot of fear at the start. But the more I've spoken to industry professionals like you, other tech professionals who've been on the channel through Instagram, there's just so much optimism and so much motivation also around this topic. And I think people are seeing that they're going to work with AI to take their jobs to the next level. And it's going to create a lot of opportunity. One thing I also wanted to say in terms of integration and to just do a shameless plug is that our curriculum editors at Career Foundry have also been working very fast in the background and have updated the full data analytics program with AI content too. So I'll just put that shameless plug out there. I'm going to ask a couple of questions. I know we're running a little bit over time, but I do want to come back to LinkedIn because Hilda's got a great question, a difficult question. Have we ever asked this one before? The dreaded moment that you're in the interview and the interviewer says that you're over qualified. What do you do? What do you do? I've never had that happen. I've never been over qualified for a position. I've heard that happen and I've thought about it before and here's what I would say. If that were me, I was in that moment and they're like, hey, you're over qualified. I'm going back to an entry-level data analyst position. I've been an analytics manager. I'm running my own company. Let's say I go back. I'd be like, hey, listen, I would not be applying for this job if I didn't see myself at this company or in this position for a long time. That's what I would say. I would say I'm applying to this job for a reason. It's because I really believe in the company. I really want to be in this role and I want to grow with this team. That's what I would say. I hope that's pretty good. Thanks, Alex. I think somebody asked whether your offer is going to be adjusted for inflation in five years. That's a question that's come up. Alex, thank you so much for presenting this evening. I know that we had a lot of questions. We do have to cut it off, but thank you so, so much. For anyone in the Career Foundry community who's been watching this evening, do check out Alex's YouTube channel, Alex the Analyst. If you click in the live section too, you'll find some past live events that we've done. We've covered a broad array of different topics, including chat GPT, networking, entry-level jobs. We've covered a lot, so do check those out and also check out Alex's videos. They're super good. Alex, you've got over six. How many subscribers do you have now? I don't know. I haven't looked. It's like six-thirty or something. Somewhere around there. If you're in the Career Foundry community, haven't checked out Alex's channel, get over there. Like and subscribe because it's fantastic content. One thing that we're currently running as well for those watching in Big Mark, but also on YouTube, if you click in the description below, is that Alex is currently giving away a 20% off Career Foundry's Data Analytics program. All you have to do is click the link. If you're not quite ready, you can also book a call with one of our program advisors to find out more about the Career Foundry program, the curriculum job guarantee, the new AI integration, everything you can ask the questions over there. Do go over there. One last thing that I wanted because I did mention the curriculum editors before is the Career Foundry does also have a fantastic blog. I'm just going to post a link on Big Mark. Do check out the Career Foundry Data Analytics blog. We also do a Career Foundry short call. If you're interested in data analytics, I'll just post a link here. A lot of links, but do check that out. It's like a five-day introductory course where you get a little bit of a taster of data analytics. Alex, we're going to be doing an event again in January to kick off 2024 and to see how hiring is going. We will have our finger on the pulse then, but thank you so, so much for joining. Thank you for all the questions from the audience. We love to see Alex's audience on the Career Foundry channel and the enthusiasm for data analytics and data cleaning that I know some of you have is admirable. That's it. We're calling it closed. Thank you so, so much for joining this evening. Alex, we'll see you again next time. Thank you so much.


Hello everybody. It is my pleasure to be speaking to you today at OpenJS World and I'll be talking about unlocking high-performing teams with open source. So let me first start by introducing myself. My name is Tracy Miranda. I'm the Executive Director at the Continuous Delivery Foundation and the recurring theme in my career has always been open source. So I've worked with the Jenkins community and before that was heavily involved in the Eclipse open source community. So in short, suffice to say, I love open source and communities. So for today we'll be answering the question, what does it mean to be a high-performing team and really what does it take? So as a starting point to answer that, I'm going to start with a proposition that today every business is a software business or at least is under tremendous pressure to transform itself into a technology organization and continuous delivery is key to this. So delivering new software features faster while making sure that your services are solid and secure is the key differentiator for almost every business today. And so we can think about continuous delivery as being critical to how teams deliver value. So when we think about those benefits to an organization, picture an organization that can deliver new features faster than its competition or picture an organization that can pivot to respond to industry and world events or picture an organization that can take advantage of fast feedback to build a deep relationship with its users. So these are some of the benefits of continuous delivery. And it's not just at the organizational level. It also helps a lot with your processes and with your teams. This is my favorite part. Like these processes help create a high trust culture and most importantly reduce burnout, which at a time when we have so much to contend with, it would be really nice if certainly in our professional lives we can do whatever we can to reduce stress and burnout when it comes to delivering software. Okay, so what is continuous delivery? It's essentially a software development practice in which teams release software changes to users safely, quickly and sustainably. I'll talk about a little bit more how this has changed recently. We have been delivering software for a long time, but the rise of microservices and cloud-native architectures has caused a corollary rise in continuous delivery practices. Continuous delivery includes the practice of continuous integration, which is, as many of you may be familiar, the practice of merging all developer working copies to a shared mainline several times a day. And before we go further in looking at this, I want to position three things that are often used in a slightly interchangeable and confusing manner, especially if you're new to the space, you will often hear people talk about Agile and then continuous delivery, or CICD and DevOps. While there is overlap, each one tends to have a distinct focus. So for instance, Agile is focused on processes. And yeah, I tapped to this great blog post from synopsys.com. And then when it comes to DevOps, DevOps is an organizational and cultural movement that aims to increase continuous delivery. So as a result, you see it will focus on culture. And then continuous delivery focuses on the tools and automation, almost seeing that as a way to drive culture change. So we have seen in specific cases you have great tools, and really be that point that helps push your team's culture in the right direction. And so for the rest of the talk, I'll be talking from that perspective of tools as that basis for driving change around software delivery. So I start every talk by telling everyone how lucky we are in this day and age and when we're delivering more software than ever, that we have this incredible research around what it takes to build and scale high-performing technology organizations. And this comes from the Accelerate book, which if you have not checked it out, I highly, highly recommend it, written by Nicole Forsgren, Jess Humble, and Jeanne Kim. And it's a partner companion to the State of DevOps reports, which they ran for a few years as well. And my favorite quote from that whole book is from Nicole, where software delivery is an exercise in continuous improvement, and our research shows that year-over-year, the best keep getting better, and those who fail to improve for further and further behind. So yeah, News Flash, Standing Still is just not an option when it comes to modern technology development. So, but the book then goes on to break down what it does take to build and scale your organization in this way. And these are in the form of 24 specific capabilities to drive improvement. So that's a lot of things to manage all at the same time. But I want to focus in on the first eight. So numbers one to eight over on one side. And these are specifically what we call the continuous delivery capability. So pulling together version control, automated deployment, continuous integration, security. These all come together to form a fundamental basis of improving how your team can be high-performing. And as you're making improvements in this space, the other thing well-spent spells out is how you go about measuring your success to see how to track your progress. So the book talks about the four metrics, so two on speed and two on stability. Unlike other metrics, these are super important because they not only kind of fall in this domain of IT metrics, but they are also business metrics. And this peer-reviewed research has shown that they correlate with high-performing teams and good business outcomes. So on the speed side, it talks about how frequently is your team deploying software? Is it daily, weekly, monthly, yearly? And then what is your lead time from the time you push to that change gets to production? So those are your two speed measures. And then when it comes to stability, you can think about it as, you know, how many failures are you having per the number of deployments? And then secondly, how long does it take you to restore services? So what is that time it will take you to recover when something goes wrong? So we have this great book, Accelerate, and we have all these amazing benefits. So we kind of know the why and we know the how of continuous delivery. But adoption is still not as widespread as you might think. And that's where we have the Continuous Delivery Foundation coming in. So there's about three things, the way I see that prevents people from being as far down in their software delivery journey as they'd like. So one is this rise of microservices in cloud-native technologies. It's an amazing game changer. It allows us to scale incredibly. But at the same time, it's a completely different paradigm of, you know, lots of environments distributed, code bases, and it leaves teams with a lot to contend with. You know, it's just an explosion of environments. And that has in turn also led to a lot of tools emerging in this place. So it's a very fragmented landscape. It's very difficult to figure out how to put together an end-to-end solution. And finally, change is hard. We all have limited amounts of change that as people or as organizations we can do all at the same time. So it's very tricky to kind of evolve our tooling and get away from technical debt. So in response to these kind of challenges, the Continuous Delivery Foundation was set up back in 2019, partly to nurture open source projects. And I'll talk a little bit more about these later. But in general, we see us as having this wider mission of we want to improve the world's capacity to deliver software with security and speed. And there's this saying we have in technology that the future is here. It's just not evenly distributed. And this is definitely the case when it comes to software delivery. But what we have seen is we believe the power of open source collaboration and use of technology can incredibly help level the playing field and make it easier for folks to get better and better in this way. So today, I want to talk to you about three ways the Continuous Delivery Foundation is approaching helping the industry and helping people who want to go on this journey to becoming high-performing teams. So the first thing is around driving continuous delivery and adoption. And we approach this with a number of different initiatives. So we have a Continuous Delivery Landscape. For any of you folks who are familiar with like the Cloud Native Computing Foundation, they have this amazing science here. Landscape also sort of known as the Hellscape and in the most affectionate way. But what we're trying to do here is zoom in specifically on software delivery technologies. Sometimes we fall into this trap of thinking it's CINCD, so it's just integration and deployment. When really there is a lot more to it, to deliver software, you need to get your testing right, you need to have potential analytics and monitoring, and security is super important. So the idea here with this, we're putting together this landscape to try and give people first a high level view of all the different options in the space opens also not. And this is all open to contribution. So if you see a tool missing, please do submit a poll request. So another initiative I want to touch upon is that we have an End User Council. These are for folks who are working in organizations who use Continuous Delivery Solutions, to put together end-to-end solutions and making them work for their use cases. So the group meets monthly to have these in-depth focus discussions on specific topics. So for example, we have a lot of folks from the FinTech space, and they'll need to talk about the specific governance and compliance regulations they need to meet with their software pipelines. We also have wider discussions around developer productivity or measuring success. And we're also looking to help drive the direction of tool development. So the people who are using the tool can give feedback to the people who are creating the tools. And one thing you'll see on our website is that group has put together an End User Council Plan where they also map out an editorial calendar of the key topics that everybody sort of agreed on. Hey, these are things we want to have deeper discussions. We want to spend time on it. It's not like they're in-depth discussions, and it will take time to sort of work out what we're doing, compare notes with other people in the industry, and also figure out where we should be improving. So you can take a look at some of the resources coming out of that group on our website. So going back to the three areas in highlight, the second one is around open source projects in this space. So the CDF launched with four key projects, Jenkins, which I'm sure many of you have heard of, and have used as used by practically everybody in different ways. Then we've also got Spinnaker, which is the incredible technology that came out of Netflix. And then we have the newer projects in the cloud-native space. And I'd like to look at it this way from an adoption perspective. So a lot of folks are using Jenkins and have been for many years, and Spinnaker has also got some great adoption. And then on the other hand, as we have cloud-native technologies and more people moving over to microservices, we have projects like Jenkins X and Tecton, which are focused on building on Kubernetes and providing options for how you can build your CI and CD pipelines and have them just with a lot of scalability and taking full advantage of all the benefits of being in a distributed environment. And one of the ways we like to think about our open source projects, so we have them at every end of the adoption curve, but we also try to push our projects to help tie to these best practices or to these capabilities. Because when we look at the list of things that the research says we need to get better at, there's a lot of things on that list. And we have to ask ourselves, is this something that software tools can help us with? Tools will solve all your problems and they're certainly not going to bring around changing your culture or making your team better, but are there some things we can trust to tools so that we can focus on the harder things that take longer to bring about change? And I would argue yes. There's a whole set of things where if we can have tools that kind of lend ourselves to more opinionated workflows, they can set us off on this golden path. So in particular with tools like JenkinsX and Tecton, we're really looking at it that way of saying can we set out with these tools that encourage best practices by default? So moving on to the third point first we talked about general continuous delivery adoption, second we talked about projects. The third side I'd like to see as the community side. So what can we do to make this continuous improvement journey easier? We talked about earlier change being hard and we're always looking for ways to make easier for people to bring about that change in the organization and have other folks to talk over some of their decisions and choices and see if they're on the right path. And one of the other ways we like to approach this is saying how can we simplify things for the whole industry? How can we make solutions easier, especially when it comes to this explosion of tools and choices? And there's a strong set of folks who share this idea that we need to promote interoperability. We need to have standardized building blocks. We shouldn't be reinventing the wheel and we should really drive for common APIs and metadata and that will kind of improve the rate of adoption and the way the industry can adopt end-to-end solutions and beginners can get started and things like that. So to that end one of our most active special interest groups is the SAKE interoperability. It meets every two weeks and we have great conversations where we're trying to bring people together, trying to find common ground and it's spinning off quite a few initiatives. For instance, we have a focus group, a special interest group on events in CI CD saying okay, let's standardize how we talk about the events you get from a CD pipeline and let's see if we can drive for different tools to all adopt the same strategy so it gives us these building blocks to build upon. And similarly, the Tecton project, if you take a look at that, it's got some great building blocks for anybody looking at continuous delivery in a cloud-native space. And one of the other kind of initiatives that sort of emerged as super important when we started those discussions in the interoperability group was this around terminology. Even as you get started and you start moving between different tools or looking at different tools, you find that different tools will use different terms for the same thing or they'll use a word in a different way and the scope is slightly different. So we've tried to capture that as well in what we call our Rosetta Stone for continuous delivery. And it's a page in GitHub which it kind of compares and contrasts the terms and it tries to drive some clarity around these terms so we can make people's life easier when they're looking at and evaluating different options for their continuous delivery. So that was kind of a whistle-stop look at the ways that continuous delivery foundation is trying to bring about this change. So striving for continuous delivery adoption, promoting the sustainability of open-source projects that help with best practices and then just bringing together the communities in ways that we can make life better for everybody through interoperability. So I want to sum up when we asked ourselves in the beginning what does it mean to be a high-performing software delivery team? The Accelerate book spells that out for us. We need to continuously improve in these practices and we measure that against how quickly we're deploying software and how safely we're doing it and how well we can recover when things go wrong. While we're trying to make those changes, microservices and cloud-native technologies have drastically changed the game so we're having to evolve while things are changing under our feet and change is super hard so it's something we have to contend with but the option for staying cell doesn't really exist for any kind of modern or evolving organization. But nevertheless, open source can come to the rescue so in a couple of ways we can think about this. One, to take a look at open source technologies, anything from Jenkins, Detectons, Spinnaker and some of our other newer projects and these help make the most of modern software delivery so you're not reinventing the wheel or maintaining software that already exists out there. And then secondly, just being part of open source communities that are undergoing the same journey really helps make life easier for everybody. And in that vein, I want to finish off by saying after OpenJS World, we also have our annual event at CD Foundation so that is CDCon just around the corner and if anything I've said today has piqued your interest, I would say it's one of the best places to come meet the community. We have a lot of interactive birds of a feather sessions as well as talks from experts and people doing their best on this journey so it's an amazing place to meet folks, learn things and also have fun in a very welcoming community so would love to welcome you to join in with us. And I'll leave it there, please check out our resources on the website or let me know if you have any questions but I look forward to joining the community building the future of continuous delivery. Thank you very much.


My name is Jose Maestri. From Miami, Florida, I took the AOC boot camp in July of 2009 and I was still in New York at the time. And I did the program because I wanted to, first of all, consider being also a lifestyle coach. I had been introduced to a lot of what the Pickup Podcast at the time was about. And I really liked what AJ and Jordan was talking about. And when I found out that they had created a program where you can be with them and learn the material and what they have learned for a week, that I found a way, as soon as I could, to be able to, just as I started college, basically, to learn this material and hopefully even bring it at the time to my friends at school. So when I started the boot camp, you know, I was thinking, awesome, got to find a way to pick a chip. But really what ended up happening was I received the kind of wisdom that you might expect to get when you're in your 40s at 19 years old. And for me, that has been the biggest stepping stone forward in just about every positive aspect, and even negative aspect of my life, to be able to appreciate everything with the lens of the, again, that kind of wisdom that you don't find often until you're older. A lot of what I've learned has been through deliberate practice, has been appreciating the showing up, clocking in for improving myself and being the best version of myself. And it has led me to walk around any space with a confidence knowing full well that I'm going to be okay. Fear is rarely in the forefront of my mind. AOC taught me that fear is a construct and that the notion that other people are better fit for things than I am is simply my way of talking myself down. We're all in a horizontal playing field. The world is my oyster, and it means that I have full domain over whatever I want to do. So if I had to explain to someone what it is that they would get out of maybe doing a program like this, specifically this one, is that there is an opportunity for anyone to understand that their self-limiting beliefs are of their own creation. And maybe you're just tired of hearing over and over again that you're just acting weird about it or that someone's telling you what you're thinking is wrong. You don't understand how there is an ability, there's an opportunity here for you to refocus how you approach your life from simply being at cause or I'm sorry, at effect of life and rather be at cause of it. I remember a specific moment where one of the older coaches, Alex Weber, he took me out through Central Park because this is still in New York. And I asked him, so where are we going? And he told me, wherever you want to go, what do you want to do? And I looked at him and I said, I want to go up the rock. Why not? I want to go up the rock that's in the middle of Central Park. And he's like, so why are we still here? And it was one of the most empowering moments of my life. So I would tell anyone that would be considering a program like this, is if you want to feel that empowerment, that level of confidence that you just know is yours because you chose it, there are opportunities. This is one of the best opportunities to be able to understand that, to be able to grasp that, to embrace it, and to carry it forward.