 Okay, please hi everybody welcome to another career foundry event this evening I know that a lot of people are joining Drop us some emojis because we've got an emoji bar at the bottom Also, we've got a chat on the right hand side. So whilst people are joining just drop your name and While while you're interested in data analytics, we want this to be as interactive as possible Alex wants it to be as interactive as possible. Obviously the emojis coming in already great great job So don't be shy Yeah, just drop your name in the public chat and if you're watching on YouTube or LinkedIn because we're streaming there to also drop Your name there to this evening. It's all about the top five emerging trends in data in 2024 We are recording this session. So if anyone misses it Or once to see recording will be sending a recording round tomorrow by email for those watching on big marker But before we kick off, let me just introduce myself and career foundry I'm William events and communications lead here a career foundry and career foundry is the online school for your career change into tech So we guide you from complete beginner to job ready professional in data analytics and help you land that dream job With career foundry programs to get a mentor and a tutor. So that's our dual mentorship model And we also have a job guarantee. So if you don't land a job within 180 days of graduation, we give you a full refund If you've got any questions about the curriculum or the program I would say book a call with one by program advisors if you're on YouTube. We've got a Program advisor link in the description below This evening, it's all going to be about trends But if you got up if you want to ask anything specific about maybe the curriculum or the job guarantee I would recommend booking a call with a program advisor and I think that's about it for me Alex. I think I'm just gonna I'm gonna give the floor to you one thing I would say is that we are having a live q&a at the end And I'm sure we're gonna have lots and lots of questions about emerging trends So drop all of those questions in the public chat Alex is probably going to pick up on some of those as we go through But I'm going to disappear into the background. I'm going to come back at the end and then we're going to have a live q&a So if you've got any questions About data analytics now is the time and Alex is the person because he has a fantastic youtube channel Alex the analyst over on youtube which is closing in On 700,000 subscribers So anyone from the career foundry audience this evening Check out Alex's channel and like and subscribe and help Alex get to 700,000 on that note Alex I'm going to disappear. I'll be back at the end and yeah, everybody enjoy And yeah, see you later Awesome. Thanks for the intro This topic i'm really excited about because um 2024 is Every year just wild things happen in the data world and so 2024 is no different. I think 2024 specifically has already been Just wild in the past month And so yeah kind of forecasting out for the rest of the year. I'm excited to talk about it Kind of be my thoughts. I think I have a pretty good perspective on this um My job which now I own uh, I run a consulting company for in data analytics I work on a ton of startups. So I got a really good pulse and really good beats on Kind of the startup world with a lot of data infrastructure companies data migration companies data analytics companies that I do consulting for But then I have my youtube channel and you know, I'm on linkedin and twitter And so I get a lot of messages of people with new technologies that are coming out and questions and there's some of the articles and I Keep up with the stuff a little too much I probably should should be doing other things sometimes, but I just get really into it So I feel like I have a pretty good idea A pretty good sense of what's kind of coming I'm some of the big trends that are going to be uh coming in 2024 If you do not know who I am my name is alex freeberg I am the founder of analyst builder for technical interviews and of my Consulting company called alex analytics and then my youtube channel. And so I do a lot of stuff And if you haven't seen my youtube channel, go check it out. It's pretty cool um, let's start off with I Specifically ordered these in a in a very intentional way. Uh, so this was not random I want to get the you know the the big one out of the way Because this one is something that I'm sure every single person out there is thinking about talking about You know always trying to keep up with um But ai specifically there are some things that I think are Going to be bigger than others For example, I I think everybody knows about like ai encoding and ai doing like summarization of text so I think that is something that Basically almost everybody's aware of at this point, especially if you're in the data world like coding You know, there's lots of different ai tools like github co-pilot chat gbt, there's you know barred and Anthropic and all these other different ai tools that you can use for for coding some that are integrated some of that are standalone products So i'm not going to go super into that. Well, let's talk about A little bit about ai and kind of the changes that we're going to be seeing from 2023 2023 was a wild It was a wild ride. It was like a roller coaster with ai When it first started kind of emerging in late 2022 there was a lot of you know I don't want to say Hyping it up a little too much But even into 2023 we saw a lot of hype around ai and whatever everything that it could potentially do there were a lot of fears around it a lot of Concerns about you know job job Layoffs because of that and You know now we're into 2024 I think people have a much better sense of what ai can do right? It isn't going to replace software developers or programmers or data analysts You know anytime soon, but it is a fantastic tool And now we're seeing ai can do a lot of different things and what's amazing with ai is that now large companies are really starting to To build out their infrastructure and build out everything they need to start using ai much better For example, I attended a conference last year near mid-year end of year in this you know fortune 500 company was talking about how they're going to be using ai across their entire enterprise And that that was the first time that I'd seen it. But then after I started You know keeping up with some of these other companies. They also were talking about something called Synthetic generated data, which is the third point on the thing down there. So I'm going to talk about that for a second They mentioned something called synthetically generated data and at first I was like, okay. What is this? How does this work? because I've never heard of it before and essentially what it is is it is Data that you can generate based off of different use cases and different scenarios For example, you have stock data Which most people are aware of it's kind of something that a lot of people use in like projects and different stuff Or maybe it's cryptocurrency You know data And so what you can do is you can plug in different what if scenarios? What if you know, we have a republican president nominated in 2024 versus a democratic president and it does It kind of forecasts based off of historical trends With that data and it does these what-if scenarios. So it forecasts and can create data For that scenario versus this scenario And so it's pretty incredible and you can essentially get it to do almost whatever you want now Is the data perfect? No But it is a really really amazing tool to test out these different hypothesis And these different scenarios that could happen This is a really useful tool. I know I worked in the medical field In healthcare for a long time working with cancer data hematology data claims data You know really In just for some context there. I've worked with a lot of clinical trials And so with clinical trials you have to get a lot a lot a lot of data You have to collect a ton of data to make sure that your outcomes are good for certain drugs before you put them on the market well With synthetic synthetically generated data You might be able to help generate certain pieces of that without having to necessarily collect every single piece Which may take you know months extra And so there are a ton of real really really good use cases where you're using ai to you know add data or Create this data for you. So really really neat. Um, so if you haven't heard about that highly recommend looking into it It's um, it really was pretty amazing when I first heard about it now I've seen lots of other companies Start to do that as well. So I think 2024 If you haven't already seen it, you'll see it more Um, especially in like financial institutions. I think finance and healthcare Are two where this specifically is going to be a really really, uh, you know, just great thing that ai can do The one up top is hyper personalization Now if you don't know what like personalization is for products think think ads, right? You go on the internet. You got a completely new laptop. You don't you don't log into anything You create like a new uh, linkedin account or instagram account or whatever it is And you start going on places and start going on websites and they start collecting that data and tracking that data And they on most these websites are going to offer something like a personalized advertisement, right? You start looking at boats online and all of a sudden you're seeing boats, uh in you know different things We've already started to see these, uh This personalization for the past several several years, right? This is nothing new especially with the the invent of Uh social media and the rise of social media. There's so much data to be collected Well hyper personalization goes a little bit beyond that It goes a little bit beyond just collecting a little bit of data to where it's Using your interests and it's using the knowledge that the data that they have on you to actually create a unique advertisement just for you Now this is just an example hyper personalization goes uh beyond that But for this example for advertisements, you're going to start seeing that are unique to you Something that No one else in the world is going to get the same advertisement as you Um, I've already seen examples of this and I'm sure maybe you have as well on social media where Um, you know, I go on there. I'm alex freeberg and so I go on to the internet and I'm typing around and it says Hey alex, you know, you live Charleston, South Carolina He's a coupon for 20 percent to this restaurant that you love or that you went to that one time It's kind of freaky But it's like Super personalized and it's hard to kind of look away because you're like this is so in tune with who you are Because they have so much data on you now imagine this for not just advertisements But imagine this for a lot of different things. Well, we've already seen Uh a little bit of this if you think Uh video games if you think social media um and Things like your iphone hyper personalization is going to be uh very very very big Especially probably in 2025, but we'll see a lot of it this year um Apple is working on a lot of these things and so, you know Do a little bit of google search on the uh hyper personalization that apple is doing. It's really fascinating It's a little bit scary if i'm being honest Um, because I see this like 10 years down the road. I'm like this What what's going to be happening this year will be you know, what kids are growing up, uh, You know in 10 years that's going to be normal to them. It's just weird to think about And then the next thing is integration into everyday tools and products now this one I kind of mentioned a little earlier for coding uh just for one example is AI is getting integrated into almost all coding uh tools because everybody wants it for example I for my company analyst builder. We use super base for a lot of our data. Well Super base has an ai tool built in for questions and I'll say, okay, you know, what uh, You know, let's think about a certain population What are the people who are paying versus not paying what what are the percentages and I can like it'll help me generate a query Does it always get it right? Uh Not always uh anyone from super bases out there listening. Um, it's definitely not perfect I've used it quite a bit and it's not it's not perfect, but it is really good Right. It helps you get like 80 of the way and you can kind of fix it Well, this is not just going to be for coding tools. Uh, you'll see this in almost everything And I'm sure a lot of you guys, uh, are familiar with google plugins Google plugins are everywhere and ai is in a lot of them And I've used a lot of them myself because I'm really interested in that for productivity and uh, I do a lot of Summarizing information because I don't have time to read 20 pages of a pdf And so we have ai that's being integrated into websites. You have it that is being integrated into Like pdfs and different tools and so this is the year that you're going to see just ai everywhere, right? And you can choose to not use it You can choose to Just do it the old-fashioned way and I say old-fashioned. I just mean like how you do it now ai is meant to be an enabler And it's going to be in almost everything. Uh, you're already seeing it on like a flight What's it called like expedia.com right you go on to expedia you go on to a car website They have ai, uh, they're trying it out. They're testing it out and now that's in 2023 and 2024 it's going to get a lot better there'll be a lot of products that are created specifically for car dealerships specifically for airline Websites specifically for all these things. So you're getting the ai that's Personalized if you want to go back to the previous one specifically for each of these use cases and that's just a It's a really really Interesting time that we're going to be living in in 2024 to experience all this because I guarantee you because I have three kids in Five ten years there that's going to be normal for them All of these tools that we're building and that are being developed and starting to be integrated into everyday products I'm going to tell them about the time that I lived before ai Before ai was in everything. Here's what it was like and they're just going to be like, oh dad. You're so old Let's go on to the next one This one is one that I've been saying for probably about a over a year now and when I first Started talking about it. I actually got a lot of pushback because Most people Have a tough time believing or a tough time seeing themselves as entrepreneurs or as individual workers. Give me one sec um I talked to a lot of people and a lot of people were like I could never do that I could never be a freelance or I could never be a consultant um because That my brain just doesn't work that way and I need to work at a company where I just have a w2 and that's what I do I started saying that maybe like the end of 2022 20 beginning of 2023 and again, I got a lot of pushback, but now I've seen a big A big shift in opinion on this and I think it's becoming a lot more mainstream and people like okay freelancing is like it's going to be pretty big And I myself I feel like I had a pretty good pulse on that just because I started doing consulting myself About three years ago and I was like I was like there's going to be a big market for this and even bigger market than there already was Um, you know in a year or two, which is where we are now Now what's leading? What's contributing to this? There's a few different things. One is cost of living The next is gen x and the third is lifestyle. Now. Why do I say these three? Cost of living is increasing people don't want to And I say people I'm not talking about every single person in the world I'm just talking about more people are starting to more lean this way because of these factors Uh, but cost of living is going up. There is no doubt about it inflation really hit us all my Everything bill for my whole life went up like 20% on the past like two years not good so cost of living is really getting to everybody And because of that people are looking for extra ways to make money apart from their full-time job And so freelancing Is definitely one of those ways if you have a skill that you can Freelance and put out there and be like, hey, I'm really good at tableau. I'm really good at cloud platforms I can really program well in r do this or that you can put that skill online and you can freelance for that skill Um consulting is a little bit different I I see freelancing and consulting a lot of people will put those two together Uh, as as like they're the same thing they can be in some instances But consulting is more like you have a lot of experience and you're in there to advise Not typically do hands-on work Not writing the code building the infrastructure building the visualizations, whatever it is Typically that's more of like a freelancer. That's what I would I usually Delineate those two by saying freelancers are more hands-on writing As if you're like hiring an employee consultants are more like high level advising and Bringing insights into a company so The next the other piece of this was the startups So I've talked a little bit about freelancing and consulting the startups are popping up everywhere I don't know if you've noticed but More and more and more people are starting youtube channels tiktok channels Instagram channels That is the example because I think that's the most visible thing that people see they're on social media They see all these new People coming up and starting their own thing and trying to start their like own little business Well, that's the tip of the iceberg. That's what's visible But all these people on the back end are also A lot of these people are building products as well They're starting companies to solve certain problems and the reason for that something that's driving that is There has been quite a few layoffs in 2023 and now we just saw another way of that in in 20 Beginning of 2024 now Is that across all of you know the job market? No But for some specific big tech companies, you know, that's kind of what people look at and they see that and so All these really smart people who are in we're in these jobs are getting laid off. They're like, I don't want to go back I don't want to go back to working at amazon again Where i'm just going to get laid off in six months or a year because the market is like just really wild And so they're like, what can I do To not have that happen again. I'm going to go start my own startup I want to solve this problem that I was working on in my previous company um, and I want to You know market that and make that a product so that I don't have to work again. I can just automate it or something um, the next piece of the contributing factor is gen X and lifestyle now I myself am a gen z my wife likes to uh laugh at because I'm running the cusp right. I'm like, I'm like right like two months before being a millennial um, and my wife is a millennial and so You know our the generations are just a little bit different I think the older generations are more like, you know company man be a union man And they want to like be with a company for 30 years. Well, uh gen X is not that way. I have already You know worked with a lot of people in gen X and they like to do their own thing They are very independent. They don't really uh, not everyone. I'm being very general not everybody But a lot of people they're the the the way that the younger generation is going is they want to be more free They want more freedom to move and travel and do these different things instead of being locked into a location And these startups and freelancing and consulting consulting jobs Allow you to do that at any age. I'm just saying gen X is definitely, you know more leaning that way If you look at, um, you know, just trends the older generations tended, you know Stick with the companies while the younger tends to be more like I want to do my own thing Uh lifestyle Is definitely changing as well. Uh, just to touch on this uh for a second on myself. I used to work in a Uh for a fortune 500 company I was in person and you know, I got to meet a lot of really cool people make great network. Uh, you know It was really great. I liked it good perks good benefits But I didn't get to spend as much time with my family as I wanted. Um, and I have three kids now And when I was doing that my kids are very young and so they were in, you know, day care because my wife was working Um at the same time as I was and so we didn't get to see our kids that much Um, not exactly the best lifestyle in the world if you really love your children And I really love my children. I wanted to be around them more and so I started consulting on the side Eventually that became my full-time job and so Now I get to spend probably 40 50 more time with my kids because I I'm there in the morning To help them get ready. I'm there in the afternoon when they come home Um at three o'clock instead of like getting home at 5 30 like I used to do Um, and it's it's awesome. It's really great. It's very free Um The next point on here is companies need to build data teams But don't want to invest an entire team right away This one actually I I will say kind of overlaps a little bit with the AI one AI is something that a lot of companies even if you're they're like not even like a huge data company Um, they they do things more like the traditional way back in the day up intuition and you know, uh Just knowing the market Well, they're seeing like hey our competitors are using AI and people like it and people are enjoying it This new feature that they add in we need to do that too We need to not fall behind in times and be you know, 80 years old, you know saying this is how we do it We're not changing our ways. We need to be adaptable. And so I've already worked with a lot of companies Probably last year I worked with maybe seven or eight companies that were Not originally didn't already have huge data teams built out They just wasn't there like their core of their business and there's more it was more about sales and the product That's what they were building But the data wasn't like a huge factor for them And so I've noticed that these companies are like well, we have to we don't really have a choice We need to but do a lot of these startups, especially Don't have a budget for it And so who are they gonna hire if they don't have a budget for an entire to hire on You know three full-time people to build this out and start making it usable and have a business impact I'm gonna do freelancers or consultants Um and a lot of freelancers who are really good at this stuff can do a lot of it on their own And they're gonna be a little bit more expensive, right because freelancers and consultants typically charge a little bit more but that one person can do a lot of this work and they don't have to pay for health benefits or insurance or all these other things and so they're not they don't want to commit as heavy into Hiring people on full-time. They can just hire these freelancers or consultants and so I think you'll see and before I go into the next one. I think you'll see is my last point here You're gonna see a lot more people Going into freelancing and consulting now one note is it's hard to get into freelancing and consulting if you have no experience It just is it's a fact You know typically those The people who hire consultants and freelancers they're hiring them to solve a problem Not to train them, right because they're not bringing them on as a full-time employee They are hiring them for a specific reason for them to solve a problem. So you usually need experience for that just as a side note This one this one has been really really really interesting to me because I've had some really close hands on Experience with this just last year. I was working with a company and Um, I at my previous one of my previous roles the fortune vibrant company. I was working on data migration Up getting everything into the cloud because everything was all spread out. We had all these data silos so I was working on data migration and You know choosing a data cloud platform and you know contracts and all these different things and so I have really good experience with that and so you know this this company was like hey, alex You know, we want to know Should our company move everything into the cloud or is there a different direction? And so I started talking in You know, there may have been someone who's better at this than me out there, but I think it was Some of the most interesting conversations that I've had around this and I you know, it was very helpful But here's the point When we started really getting down to I said, what's your mate? Like what is your goal with this? They said we want all of our data in one place and I was like totally get it Absolutely understand and then they said security is like our number one thing, you know, we've had We we've just heard horror stories of data security and all these different things I started asking more and more and more questions And well by the end of it. I was like, you know I'm a big believer in the cloud I'm a big believer and as are a ton of other companies. I was like but for your use case I don't know if I'd recommend The cloud for you guys because we looked at their budget We looked at their trends for or you know, their projected revenue I was like, I think I would just bite the bullet and You know do everything on prem because it wasn't a huge company and I was like, you're gonna have exorbitant fees for your To build out your infrastructure and then also maintain it and we were looking at like aws I was like, that's gonna be a lot of money a lot of money and I was like for what you guys are doing I don't think that's what you need. I was like, I if it was if this was my business And I'm trying to help you run this as if it was my business too I was like, I would just bite the bullet pay the upfront costs of building an on-prem server or servers for them and That will by far be an incredible investment have better security less downtime less dependency on a cloud platform And some of these things that I have right here are the exact reasons why I recommended that For them So let's talk a little bit about why it's called the great cloud divide right now There has been a huge uptick over the past 10 years with cloud platforms. Just massive Multi multi multi billion dollar revenue streams for all these cloud platforms Specifically the ones that most people know is google cloud platform aws and azure Just massive, right and There's a lot of reasons why people want to go to the cloud. It's easy It is genuinely pretty easy to get up and to use these platforms in general You get to put all of your data in one place Maybe even easier than doing something like an on-prem server and uh, I would say that When you're kind of spread out when you're a larger global company It's easier to connect to all these different places and give access to the data, which is very important Now the downside of cloud platforms is there is a massive amount of cost Um associated with cloud platforms, and it's only going to go up It's only going to get more expensive There's no there is no Possibility in my mind that we will see a decrease in prices for cloud platforms in the next five years It's just not is never going to happen um and so These cloud platforms there they typically will have a lot of incentives for you to get into their ecosystem But then once you get in you were going to have a ton a ton a ton of fees and costs associated with that So just to give you an example if you've never seen like these memes before it's usually a guy who's like You know opening a envelope and he looks at it It's like this is my aws bill and his eyes get huge and he's shocked and he's like like this is insane It's because aws is not like just as as an example aws is um Typically you have something like an auto scaler where you're scaling certain features and you can't always control what you're going to Pay right and so for a lot of these companies they turn on these auto scalers and like hey, you know if it costs 500 bucks no problem. It's 500 bucks 500 bucks 500 bucks then one month something changes um whether aws tells you or not or you're you're uh where you're You know ingesting the data or whatever changes and then the next bill is like $3,000 or $6,000 or $10,000 I've heard instances where a bill normally was $10,000 went up to a hundred thousand dollars that is Very very scary And so yes, usually they have incentives to get you into their ecosystem But the long-term operational costs for these cloud platforms are very high Which is okay. If you're like a fortune 500 company a big company There are good plans even for small startups a lot of startups use aws and azure and all these different cloud platforms But long term it just it never it always goes up. It always goes out. So because of this because of that piece of it There is this growing movement towards more on-prem servers for people's data and on-prem servers are just They're servers, right? So like in the cloud they have all these server farms where it's literally tens of thousands of servers running at the same time And when you use their services, they allocate you a specific server that you're just kind of like borrowing You're just like renting out a server essentially um With buying a server you're you're it's like taking one of those servers or multiple of those servers And you're putting it on-prem which means on-premises You're you're buying a physical server that you get to control And it's a little bit of more upfront cost Typically, you'll need someone who can Work it and run it. So that typically is like a single could be a single person or an it team Who actually runs and maintains the server make sure everything's you know good in the databases and and with the data Ingestion the server is running well and it's a little more upfront cost 100 percent But if you kind of look further ahead A lot of these companies are looking further ahead and they're like our aws bill is going to be 75,000 per month if we continue down this road But if we spend $250,000 now It's going to only cost us like 10,000 a month for the next 10 years or you know, that's like a rough example But I've had those exact conversations with many companies and it is this growing growing movement of yes, the cloud is still growing But you're now seeing a lot of people just bite the bullet and be like I can't we can't afford The our aws bill for the next five years. Like it's just not feasible. So That is that is definitely a big reason it's just cost the next things are internet dependency and downtime for Cloud platforms you are dependent on their services if their services are down even for 10 minutes Sometimes certain companies cannot they cannot operate effectively for their product or their customers with any downtime Now downtime can happen with your servers that you buy on prem, right? But most likely you're going to be in control of when that gets back up You have somebody on call or you have somebody in the office who can Fix that quickly You are not in control when it is in the cloud You are fully dependent on them and that is a problem for a lot of businesses They cannot afford to have that and they've been dependent on it and they're like we can't do that anymore Some companies aren't like my company or not. We are Reliant on aws being up, but if it goes up or if it goes down, it's You know, we have backup redundancies in place And so these are all things that you need to be thinking about with you know, these two different options the last one is data security Most people would agree and I would say most I'm going to say all that on prem servers are going to be more secure than cloud platforms Your data isn't sitting on some server where someone else can go access it. Your data is with you on prem You know controlled by some type of database administrator or something like that Much much much more secure typically in general And so the cloud is going to grow but we're seeing a larger move towards on prem The next one is the year of documentation and governance. I don't know why I named it that I just thought it'd be fun This one relates A lot to ai as well All these, you know, there's a little ai and everything These days 2020, you know, what can you do? People are realizing and and I remember back when I first started about seven years ago documentation wasn't like That's super important. Especially like some of the smaller companies. I first started working for I was working at a non-profit And that healthcare and lay with company when I first started out the documentation wasn't like super important um But with the rise of ai teams are like wait a second Our data is important. Yeah, we realize that but now ai can do more than just work with our data Ai can have context and it can have processes and procedures and if we actually wrote that out and had Some guidelines and we could put that into ai it would just help with it understanding our data even more and so um, I know multiple companies, uh, that are you know, uh, just off the top of my head Excuse me conva and figma are two really big tech companies Both of them came out with, uh, you know I don't I don't I don't know what the word is. Um Not newsletters just like announcements being like we need we're we're doubling down on uh documentation and governance For those specific reasons. Hey, we're introducing all these new features and these new things But we need to get our ducks in a row for it to be really effective and useful and that's there's that's just two examples There's a ton of other examples Uh, and so what I wrote here was that Governments and companies are cracking down on their data governments and compliance because Historically, it just hasn't been crazy important um and it is shocking if you really think about it because Just with the documentation piece What used to happen is is there was two or three people who had it all in their head Well, two of them would leave. There's only one so the one guy would train the other people just Through training right hands on training. There was no documentation at all like just none Um, and those days are still here, right? They're not going away, but you're seeing a big wave of people who are realizing for their use cases for Especially when using it with AI that they really really need that now the next piece is Uh data governance and compliance and data governance and compliance usually refers to, uh, a lot around how you're actually Protecting your data the data quality Um access to your data. So there's a lot of different avenues and pieces of that equation but data This has been said since, you know, uh Maybe like 2010 or in that era of social media coming over that data is the new Data is the new oil data is the new gold because it is so incredibly important um With everything that's happening in AI with all the security or security breaches and leaks and data All the issues that people are having with AI trying to use their data They're realizing that their data is one of their most important assets And so they're really cracking down on security compliance They're really trying to utilize that as best as they possibly can because I mean If you just take a step back and you look at what's driving your business for a lot of these companies It's the data and they need to get it under control and 2023 we saw a big surge in this This year is a year where you're going to see a lot more companies making announcements Hey, we we did this initiative to secure our data We did this initiative to make sure that these things are done And they'll tell clients because clients want to know if we're using your AI products that your data is good on the back end And so that's kind of like a It's a reassurance thing, right? It's only going to be more important in years to come The last thing I'm just going to read this is documentation allows for better compliance data quality management and risk reduction kind of some of the things I said Oh, I'm talking too much. I'm already 37 minutes in I'm gonna have to go over will I hope you don't mind Well, I'll get to I'll try to not talk too long and I will have time for q&a We'll do that all right data unification data unification is Really the and I mentioned a few times but the idea that You can really use all your data now I read this I think on like a medium article. So don't quote me on this I don't know if this is 100 true, but it it basically said The average company uses about 30 percent of their data And the reason is not because the 70 percent of their data is bad The reason is because all their data is so spread out Only certain people have access to certain pieces of the data in excel files In different databases and it just can't be all used which is really You know if we're talking just about before how data is the new oil data is gold Then you're only using 30 percent of it. That's not good. That's not a good thing and so Data silos are kind of this term that most people have heard of where it's like I have my data in a silo over here I also have data in a silo over here. We want to use both of them But because of how we've set up our systems This is in some weird database over here. These are just in pdf files and excel files and You know some one drive over here We can't use them. We can't connect it and use it even though we really want to Or if we do We have to export it into like excels merge it together With a manual process upload it to this sftp which then automatically ingested into the system I'm not Actually, let me take that back. I am speaking from personal experience I was going to be I was going to try to say something funny I that is absolutely what I used to do or have to do with some previous companies before we set up some more automation In our processes. That's how a lot of companies are and Just as all these other things data is becoming so incredibly important People are like we can't sit around and not use all this data That could be beneficial in this area or this piece of our product or this for our customer service or this or this We need to bring it together and we have to do this now There's a lot of different avenues for this But one that I think a lot of people have heard about or or you know looked at or something like Microsoft fabric Which is meant to literally put all of your data into one place and it's meant to keep it Extremely organized and of course that's under the Microsoft umbrella, which has a really great brand recognition and You know that is exactly why they designed this now There are other products and tools that you can do this that may have already come before that But this is Microsoft's version of this and they have something called one lake um I think I wrote it What it does at the bottom it says this one data lake which a data lake is Had was a huge buzzword about like seven eight years ago Data lake was a huge buzzword. It's like hey, you can just put all your data in here and you're gonna have access to all it It's amazing and then people realize they're like wait a second We don't know how to actually put all of our data in one place and create the correct schemas and and Data architecture to actually use that data. That's our fault. Um, we're not going to use data lakes anymore So it kind of like it was a huge thing like a huge movement and then it really fizzled out But it's still a great concept and that's what Microsoft fabric was trying is trying to do And so the one data lake uh, it's meant to be for the entire company the entire organization to have one one copy of data from uh, uh multiple analytics engines running at the same time so you don't have to um You don't have to get it from this database and pull it in and get it from this database pull it in merge It put it into this data lake and then do all this it It allows you to access the data where it is pull it in read it query it use it all in one place That's the idea these types of systems are going to be a big hit With a lot of organizations. I would say specifically small and medium size initially the large companies are always going to have an issue with this because You have years of data trauma an infrastructure trauma an architecture trauma that is going to take a long time to unravel so uh, larger companies will have a harder time with this but uh small and medium size companies should be able to utilize these very quickly um, and it's just It is something that I wish I had known about or was kind of around back when uh, I was in analytics and and as a manager because These are the exact issues that we're really difficult to solve They're really really really difficult to solve. How do you get this data over here and this data over here to connect? It's a universal problem. Um, and so 2024 you're seeing new tools coming out. You're seeing people really working on this because again data is just Incredibly important. All right. This is my wish list This is what I want to see in 2024. Um um The first is Uh, I want hyper realistic Virtual worlds where I can do my business meetings in because right now I have to do it like this Where i'm doing like a webcam. It's not ideal. Uh, it's not bad. I don't mind it But I do have a VR headset. Uh, it's not here, but I do have a VR headset I mean, I'm over here in the metal world. I'm living it up But it's just not good enough. Uh, it's just not good enough for me. I want something That's hyper realistic and for other people to be able to access and do it as well That is what I want. The next thing I want is a robotic super intelligent assistant that helps me with Essentially living my life. I want it to follow my laundry and then I also want it to respond to emails That is the dream and that is what I wish for 2024 And the last one is real-time brain decoding for instant analysis aka what neural link is doing I just need to sync up with elan And generally I think I could boost my productivity by like 200 percent I think if If I had something like that I would be the most efficient person in the world. That is our future. I just want it to happen now So I think that's more than reasonable. I think that's more than fair. Um, of course, I'm being a little bit Facetious or hyperbolic or whatever, uh, term you'd like to use but a guy can dream No, that is all I have And I think will is going to come back and we're going to do some q&a I went a little fast to the end. I could talk about these topics for each one of these topics I could probably talk at like an hour on uh, and so I try to I try to limit myself Alex, I think we can see the passion shining through I love it when you go do the deep dive But I think it's great to get completely lost in the topic With everything that you said and all of the trends that you've mentioned Is now the right time to start off as a data analyst um, you know There's there's good and bad and what's going on right now. I would say the bad is we're seeing more layoffs the economies a little down definitely Not It's not great just with inflation and everything and the layoffs. That's not great um, but That's unfortunately. Unfortunately. That's just kind of how things go every so often. This is a site This is a cyclic thing that we if you look back. This is not new to 2023 or 2024. Unfortunately So there is we're kind of in like this little dip right now. I do think things are going to go back up I I if you just historically that's just how things go unfortunately in terms of Is it actually a viable career for the future 100 percent? I think you're going to see um A lot of people joining and coming into into the data world For the long foreseeable future. I I absolutely don't see AI replacing People en masse like we used to worry about back in early 2023 I think we really understand its limitations and understand what it can and can't do right now and even with improvements even with a lot of improvements I I was listening to um Sam Altman who's the CEO of uh open AI. He was like You know everyone freaked out and panicked uh in 2023 and now all they're doing is complaining about how slow it is And how it doesn't give good outputs and how it's terrible. He's like people after a couple months. Um, you know, it's just become like part of their Tool chest and he's like it hasn't replaced anybody really and so he's like, um You know, I he was specifically talking about agi He's like, you know one of these days and five ten years will hit agi It'll be mass panic for two weeks and then after that people will go on with their lives and do what they've always done Um, and so I I I'm not as like on that side. I definitely think it it will play an impact But I absolutely see uh, there being more jobs created with AI and more teams and companies Opening up their doors to data professionals than have ever before and so I personally I think we're just in a bit of a downtrend um And you know, that's it is unfortunate I hate this like I don't like seeing when my friends and and people who I know lose their jobs And I have recently it's it's not fun to see but There is going to be an upswing and there is going to be a big Drive and push back into the you know data world and not too long. I think Awesome, thanks for that. Um, if anyone out there's got any questions on youtube or linkedin Now's the time to ask also on big market in the q and a tab Do drop them in right now and I will go through them Um, I know this evening. We've got a lot of people who are watching who are thinking about maybe transitioning into the field of data analytics How do you think given these trends in AI given? Trends in the job market. What do you think? Positions like for the beginner, you know the entry level positions our companies looking for Different skills. Maybe are they are they honing in more on soft skills or cross functional roles? Are you seeing changes in the market at that end? I I I haven't seen them myself. I just anecdotal anecdotally hear them here and there I get a lot of people reaching out to me. Um, who are like, hey, you help me get a job Here's how I got it and I hear and I read their story And it usually not always but I've heard a lot of stories like this, which is hey, alex I learned a lot of skills from you But I used to be a nurse and I used my nurse My nursing background to get a job at a healthcare and illness company almost very similar to me I see a lot of that for a lot of different domains and so I think If if I were to kind of read into that which I you know Again, I don't have like a ton of hands-on experience with that Specific thing. I would just say that I think domain knowledge is going to become more and more and more important Whereas maybe seven eight years ago It was a lot on the skills, but now with You know skills being more widely available to learn and AI being able to help with the coding pieces a little bit here and there Uh, uh, AI being integrated into things. It's more about Truly understanding what the data is telling you what it means And if you have experience like domain experience in a certain area and you're able to transition that into analytics That is like that's going to be like a golden ticket Um, and that's why I've I when I had about a year ago I stopped doing about a year ago for two years. I did mentorship The people who I saw who were the most successful with transitioning careers were the people who had experience in a field already So they were you know, one was a lawyer one was A warehouse worker so he worked he understand logistics pretty well because of the kind of work He did one was a teacher one was a nurse Every single one of them were using their background in some way to transition into the career into analytics And I truly believe that that is only going to become more important in the future A fantastic answer I would say it mirrors exactly the experience than the graduates that we have through career foundry Those with different backgrounds transitioning into a new field A lot of people think that they're going to be starting out scratch with zero skills But actually you're bringing a wealth of experience from your previous position Into your new position and you will see things with different perspectives. So great answer there I'm diving into big marker. See joanna's got a great question specifically about ai How trustworthy is ai and ai tools? Can we always fully rely on it? No And I would not I I've been using Ever since chat gbt really became a thing like a thing that most people were using back in like late 2022 I've been using it very consistently. I used it today. Um, and well And I've tried different variations. I've used bard and anthropic and Get up co-pilots and different ai systems and tools here and there. Here's what I'll say is I absolutely think they will but even right now I have so many issues With using ai almost every time I use it. It never gives me what I want You have to really you really do learn how to talk to it to where it understands what you're trying to do But even then even if you give it all the context in the world all the information in the world It only knows what it knows. It's not like this all-knowing genius That just is like Einstein level in every single topic It's just smart in every single topic and has a wealth of data and information to pull from But even just looking at coding I have gotten I've gotten more frustrated at using ai for coding than I have been Just doing it myself because In my head my perception is is ai should be able to do this because it's not that hard because I've done this before And I could have written it myself in like 30 minutes or an hour And I spent an hour trying to get ai to do 90 of it and it got me like 60 of the way there And I'm just super frustrated. So I end up writing it myself. So Just for coding that's an example with coding, but you'll see that with a ton of stuff For example text summarization. I use text summarization a lot. I have a tool on my browser that When I'm on a website, it'll it'll generalize it and I like it and it gets the bullet points But then when I'm like skimming through the article, I'm like, wait a second That's like super important and it didn't even mention that in the summary and I get I I get mad at the ai I'm like, hey ai. I'm like, why didn't you include this as like the most important part and they're like, oh, yeah No, I should have included that. Sorry about that. I'm like it the more you use it That truly the more you use it the more you realize its limitations and it has a lot um, especially with As tools like these these tools become a lot more Uh, commercialized They're getting almost a little bit dumber Um, because they have to limit themselves for liability purposes. So like chat gbt You've probably seen this on twitter or x or linkedin or wherever They're like, hey, why is chat gbt giving me answers like this now because this is worse than how it used to give me They have to do that for legal purposes and so um I only think I genuinely think you're going to get in the future better answers but those limitations are only going to get worse because um, right I keep up with a lot of ai stuff right now. They're they're the uk Uh, a lot of european countries america canna are working heavily on restricting Uh ai models and how they're used and all these different things which whether you like it or not is going to Change how they work the responses. They're allowed to give Things they can do legally and so you know, I I There's just so many different aspects to ai that it's hard to get into all of them I just don't see ai ever being like this perfect one tool that does everything It I just at least not not now maybe like, you know, 10 years will pop some of them pop up And i'll be like i was like that really could work that really could be the the one tool for everything But now absolutely not not even close I think linking on to the ai track. Rita's also got a great question Considering the pervasiveness of ai what type of uses should someone trying to enter the market as a data analyst? Should practice or or get um experience with related to ai? yeah, that's a question that i've Had with a question i've answered with a lot of different people who have messaged me who on this topic They're like hey, is it even worth getting into the data field with ai and every single time i'm like yes, absolutely How I recommend like learning about it or using it is for usually two or three specific things The first one is just coding. I think It's just really lends itself well to help you learn how to code Not it I've tried to get it to like teach me coding But it only goes so in depth and you have to kind of know already know how to code for it to really teach it to you Well, and so it's this you know juxtaposition there, but it can help you understand a lot of concepts and give you examples Which is really great But in if you're trying to use it like how you use that as a data analyst for coding, you know, you'll say Here's an example of some sample data How would I get this in my sequel? How would you write this question in my sequel and then it'll write out the code for you You can test it in your mysql database and you can Try to see if it works if it doesn't you can go back to ai and revise it or you revise it yourself So that's just one way of coding The next thing is I would say is it's really good with brainstorming ideas for data analysts In the real world things are very very nuanced and very Um It's not black and white. There's a lot of gray And so oftentimes you'll you'll have this scenario where you're like When you're learning just on yourself by yourself or on like a platform It kind of is you know, it's catered to help you learn But real world scenarios are very different Where you're like, is it best to do this or is it best to do this? Because those are two very different things which will change how I Get the data how I clean the data how I do all these things which is best Well posing these things into ai I found to be very helpful with brainstorming ideas because I'm like You know There are pros and cons of both. Tell me the pros and cons of doing it this way versus this way Um, or tell me what other options I may have besides these two options and it really helps me like Think about how I'm going to solve a problem and so There's more examples because I I don't want to talk on that question forever because I can just keep going But just those two examples genuinely you can practice that today Um And you can start working through that get a data set from Kaggle put it into a database put it into A python data frame put it into r put it anywhere you want and try to solve it using ai try to ask it questions Try to have it do things for you. You will see the limitations quickly the the more you play around with it the more limitations you see and It's a good thing I think it's a very very good thing for newcomers to see the limitations that ai has because most newcomers are like ai Can do this and I don't have to I won't be able to get a job But when they actually start messing around with it and trying it they're like, oh Yeah, no, I get what alex is saying like This this they can't really do this piece or this piece or that piece and So it's just it's good to it's good to get that hands-on experience with it Awesome. Thank you. And uh, just to put a shameless plug out there We have recently updated all the career foundries program with ai So we are ai enhanced especially on the data analytics program Shout out to a career foundries curriculum team who've worked very hard on that in the background I'm going to switch over to youtube. Hi everyone over on youtube alex's audience There's a great question come in uh from aman I've been working for three years as a data analyst What makes the difference between being a data analyst and a senior data analyst? So when we're looking at career levels Sure Yeah, I um I was never a senior data analyst Just so everyone knows I never was I jumped straight from a mid-level data analyst and do a manager role It was very odd. Um, so I never got to fully experience that senior title although I think I I Definitely was at the level of senior I just Didn't get that paid jump and that's two years that I did and I just went to be a manager But here's what I will say when you're a beginner when you first start out There aren't a ton of expectations Uh, you get into the job and it's like, you know, hey run these queries for us debug this You know make sure this process is working right and you just kind of you learn you're there to learn You're there to grow and the company is hoping that you'll stay with them a long time And um, you know, it's a good ROI well When you become mid-level the expectation is is okay, you're going to take on some more serious projects. You're going to take on um More important work and we shouldn't have to baby you as much You should be able to do most of this independently. Like that is definitely an expectation You should be able to do this independently. Maybe you're even kind of somewhat mentoring a little bit like the new people Um in your company So if a new person is hired on as an entry level that you're there to kind of like support them and help them um, then you get to senior and the senior level is You are expected to work on your your um The work that you are doing is expected to be a very high level of Difficulty um as well as collaborating with a lot of other teams in order to make it work for example Um, you know back just when I was a mid-level, but again, I I definitely was I would say I was more like senior level Even though I didn't have that title I was taking on big big big projects that had you know million dollar budgets And you know, we'd be working with three or four different departments on these projects And all of us are working in collaboration And it's really advanced and really really tough data pipelines that we're trying to create and we're working with Uh, just it's very very difficult, right? You can't you couldn't give those types of projects to mid-level or entry level It it would just be too complex. And so the the technical skills have to be much higher for senior level Usually the domain knowledge is also much higher Um, because you have to know the data inside and out That's back when I was working with hematology oncology data. That was my specialty Like I knew that data inside and out. I knew it extremely well How it originated how it got into our systems how we used it for all of our products and all of our different things And so it's just it's a knowledge thing with both skill and with domain and then you Really should be working incredibly independently and helping mid-level and entry level That is that is the difference. And so you're just working on a lot more important work That has a bigger impact on the business because they know that you can handle it and they trust you Whereas mid-level especially entry level, they're not going to give you those big projects that are worth a lot for the company because You know if you mess up or you don't know what you're doing or you haven't had experience with it You know, there's no there's the lack of trust And so senior level they should trust you know that you're going to be doing a really good job And you know what you're talking about Awesome. Great. Thanks for the answer. Um, also a couple of questions that come through about portfolios I've seen the question by Bianca on big marker um and Just looking here also with uh, you know, looking at how the industry has evolved with AI looking at trends Um, what is the relevance of a portfolio in the industry? Um for people who are thinking about transitioning into the field? Portfolios are still really important. Um, I don't see them going away anytime soon I still have a portfolio. I updated it a couple months ago with a new project that I built Um, not for anybody. It was just me. I was just like I had an idea and I built it and I never told anybody about it I added to my portfolio because um Even me I need something to demonstrate my work. I have my youtube channel. I have all these things so I still work with you know, uh people and um Portfolios are Um, I would say they're still extremely relevant in the fact that even with AI You need to demonstrate your skills. So they don't want to hire someone who Doesn't know the skill that they're hiring for it's as simple. It really isn't as simple as that for example, like At a previous job, uh, I was on the hiring team We would test for a sequel or power bi or you know, whatever we were testing for um, and if they could demonstrate it in a project it made them just The conversation flowed so much easier in an interview for example with power bi Power bi is a very simple tool on the surface. Um, very easy user interface But using it in the real world is actually pretty difficult. That's why they're called bi developers not bi visualization specialists for the most part because they're working with a lot of Data pipelines and a lot of different things to create the data and make it good for the visualizations And so when we would hire for these These people if they had a portfolio and we could just see what they've worked on and be like, okay How did you do this and they can walk us through that? Every single time someone did it I could I could tell right away whether they really knew what they were talking about or they didn't If they didn't have a portfolio It's harder to engage in that conversation and really understand what they know and what they don't know Um, and so I have always felt and been a very big believer in portfolios And I don't see them going away anytime soon. I think they're still very relevant Just to touch on what you said earlier in data analytics, how how much web development skills front end development skills come into play? um You mean like visualizations? Yes, with data analytics very wide range I literally have met people who are data analysts who literally only worked on visualizations They were like What what I would call like a visualization specialist. They have the title of data analyst But I've met people who do only visualization I've also met people including myself who did zero visualization for some of my jobs Now my first two jobs I did data visualization in tableau And then when I became a data analyst at the fortune 500 company I was doing data collection So we worked with You know etl pipelines and you know data migration and all these different things I didn't work on the visualizations at all. That wasn't my job We had bi developers and then I would go to the bi developer I'd say hey, you know, here's what we need for a client. Um, they would build it out I would review their work before I hand it off to the client. I'd say, oh, okay Let's actually change this we need this data point instead of this. I didn't actually build it at all So it varies widely. I think there is usually a happy balance somewhere in there for most data roles Um, especially at small companies where you do everything, but at larger companies, um, there is a usually a happy balance where it's like 80 percent not visualization maybe 20 percent visualization or More often than not I usually see it like it's 10 percent visualization or you know 15 percent visualization But a lot of it is in the data using uh databases working with clients You know Different skills other than just visualization. It's usually a smaller percentage Fantastic. Thanks for that. I'm just going to jump very quickly and I am mindful of the time here We are pushing on for anybody who's interested in maybe learning more of a tool We have got a career foundry mental who will be presenting another presentation a couple of weeks Dr. Humaira who is a machine learning expert based in munich and she'll be doing a deep dive into sql I've posted a link on a big market But maybe someone from the team could just take that link and also post it on youtube too Alex there was another great question that came in on youtube from one of your audience and it picked up on Something that you mentioned about clay a cloud data analytics before Shane is asking what are the skills required to become a cloud a data analyst Sure. I'm not surprised. That's a great question. I'm not surprised. It came from my youtube channel. They're very smart people over there What I will say is is oftentimes Most people don't start out in the cloud right away. Um, it It just I've I've worked with a lot of people most people who I've like either mentored or talked with They're like, oh, yeah We start off in sql and then you know, then I moved to a company that used this or then I moved to Our company migrated to this so most people don't start out in the cloud Um It just from my experience But as more companies move to the cloud like we were talking about earlier I think it's going to be This this year is for my youtube channel. I'm going to be focusing a lot on the cloud I'm going to have a whole series on aws a whole series on azure Um, because I I people need to start learning it for sure So what do you need to know? Usually there's about three main components that I think are really practical to data analytics One is something like azure data factory. I'm going to speak specifically on azure for this use case. Um, azure would be Or for this example azure Does a million different things It genuinely does you go in there and start looking at azure. It is overwhelming the amount of things that they have But specific to data analytics, um, azure data factory is for like etl pipelines and and ingesting data I worked with azure data factory for like two years straight. Um, and you know, it's It's a little bit more advanced. It's it's not something I would start out in that's I'll just as a You know a side note I wouldn't start with azure data factory, but it's something that one of the three things that I would learn Um, the other thing is just working with their databases So they have databases. They have data warehouses. They have data lakes I would just start with the databases if you know how to use the databases Usually you can pick up on how to use the warehouses and the the data lakes are a little bit more complicated With how you're actually working with the data and use it because then you got to connect to something like data bricks and use it Maybe like something like pie spark But that's a whole different that's a whole different conversation Maybe we need to do another webinar and just like cloud platforms I can do like a deep dive and like azure and aws because that I could talk about that for a long time um and then and so I'm gonna I'm gonna take it back. I'm gonna say just those I would just start with those two start with data ware Uh, data bases and data warehouses Just start with that learn how to use it learn how to put data into it from like an excel file or connect to a data source Just start out with that Then learn about azure data factory. Uh, that's where I would start now. There's so many other aspects Um, the azure is a huge ecosystem. So it can be very overwhelming I would just start with those two and then you can branch out into other things like I said, you know There's data lakes and and data bricks that's integrated in there and there's just so many things. So Don't get overwhelmed. It can be overwhelming. Same thing with aws aws. Maybe even more so but don't get overwhelmed just ease into it with a database Like you should be somewhat familiar with if you've used like my sql or microsoft sql server Start off there and figure that out and then move on to the next stage Awesome I'm mindful of the time but there's there's some really great questions on youtube I think we should do a quick fire. I think we should do quick fire alex. We'll try Yeah, we'll try this out It's a new format. Okay Shabin is asking if you were to choose only one data analytics tool for the next 10 years What would that tool be? SQL all right next question right Cheyenne, sorry if I pronounce anyone's names wrong Cheyenne. It's asking what should I learn for front-end data analysis streamlit or dash Uh, I like streamlit myself. I've used dash 2 and it's also really good. I just have more experience with streamlit I think it has a really good community around it Fantastic Gonzo is asking what are your thoughts on learning coral language before any other data language? I'm not super familiar with that. So I'm going to say path I think we should add the pass button too. That's good Zero do you think gemini ultra is needed to speed up learning a way or is it enough to use chat gbt 3.5? No, you can use I I would say even them even like chat gbt 3.5 is perfectly acceptable. Um, it does a very good job now Okay, this is supposed to be rapid fire, but you'll see improvements with chat gbt4 And you'll and it maybe if you're using the api, it's going to be a little bit different But you don't need the latest and greatest with ai right now Maybe the few maybe in like a year you shouldn't be using 3.5, but 3.5 perfectly acceptable to use and it's free Awesome, and then robert's asking is learning excel still worth worth it given microsoft co-pilot? 100 percent 100 percent in fact, I'm making a video right now on microsoft Co-pilot because I you know started paying for it and using it um It has a long way to go and excel is like the de facto tool in any company For businesses all around the world it you have to know how to use it. So yeah You'll see my video not too long on that maybe Maybe next week maybe the week after but There's a lot of there's a lot of issues with it right now They there was a reason why it was delayed for like six extra months or like eight months when they said that it would be coming out There's a reason and it's it's still there. Um, and so no, I'm not don't don't put your faith in github Or uh microsoft co-pilot right now So robert this goes out to you. There's no way that you can avoid microsoft excel He's still got to learn it. He's still going to learn it. It's going to be there Alex, I think we're going to end it there. That was some great questions. Thank you so much for the answers Thank you so much for the presentation As I said before at the start anyone watching on career foundry on any of our channels do go and check out uh, alex's youtube channel alex the analyst and help him get to 700 thousand But also, um, he's got some great content up and coming So do subscribe to that if anyone's interested in data analytics anyone's interested in career foundry Um, I've just been a post on big market a link to book a call with a program advisor We've also put it in the description below So do have a look there if you've got any questions about jobs in your locality Our curriculum the dual mentorship model guarantee that we have Do book a call with a program advisor and get your questions answered We are currently offering a 20 off career foundry's data analytics program I've added a little sticky note on big market, but I think it's also on youtube So to claim that simply click there and it'll take you through to the discount alex I'm sure we're going to see you again on the channel. This sounded fantastic I think we should do some stuff about cloud platforms Um, I think we should we should go into some new territories. I think um, but thank you so much for presenting this evening and thank you to alex's audience too for joining us and We're going to be sending around the recording tomorrow by email But you can also see it over on alex's channel if you get to the live section You can see that and also some previous webinars that we've done together over The past 12 months. So, um, yeah, thank you everybody and um, it's time for dinner for me But we were something that's probably breakfast time or lunch time and alex