Watch Me Build a $100k Data Analyst Portfolio With AI From Scratch (To Get Hired)

This video, we are going to be building a $100K data analyst portfolio from scratch. Going to show you the best way to source really good projects that are not from Kaggle. What I'm going to show you how to do is also do all of this with AI. I'm going to be using Mantis because I love Mantis. This is my favorite AI tool. You can do this with any AI tool. You can do this with Claude. You can do this with ChatGPT. But we're going to be using Mantis to be sourcing, finding projects, sourcing our datasets, and also helping us do some preliminary work as well. All right. So when it comes down to our portfolio, it's all about having high-value projects. And high-value projects are all about pretty much projects that cover business problems and things like that over, you know, high-value business properties per se. So for example, retention. When it comes down to business, there's, you know, 3 Rs, 3 main Rs: revenue, retention, and risk. Pretty much every business problem or any person in a business, your work is supposed to be tied to any of those 3, whether it's going to be increasing revenue, reducing risk, and increasing retention. That could be both employee retention, also customer retention, right? And all of those all relate to the bottom line when it comes down to revenue. Whether you're doing a nonprofit, working at a nonprofit, or even a for-profit company, it's all about staying in business. And to stay in business, you have to be profitable and you have to make revenue. So you want to build your projects around, you know, those things. And a great way to do it, especially when you're a career changer, or a way to step away or step above like Kaggle. One thing about Kaggle, like I used to really like it when I was first getting into data, you know, 5+ years ago. But the thing about Kaggle that is a knock is that there's so many people, like anyone could like upload a dataset in Kaggle. The quality could just be a lot of like really fake randomized datasets that's like not really worth your time. All right, so when you're trying to get your first analyst job, there's 2 types of projects that you will always be working on: projects for practicing and then projects for showcasing. I would say, what, 80% of your time you'll be doing projects for practicing, for, you know, when you're learning Tableau, learning SQL, where you're learning these new skills or tools, you're going to be doing, you know, projects and challenges, things like that to develop your skills. But projects for showcasing, that's completely different. That's just like, you know, the difference between getting dressed to go to Walmart versus like getting dressed to go to like your prom, right? You go to your prom, if you did go to prom, like, that's like you get dressed up very well, very fancy, spend a lot of time getting ready. That's like once in a while or whatever. That's just an occasion. But you know, you get dress to go to like, you know, Walmart or whatever, whatever it is, like often. So it's a different level of preparation basically, and time commitment. A lot of people will put these very projects that they did for practice that's not very polished on their portfolios, and then they wonder why they're not getting like callbacks, and then why they're not getting like the reaction that they would like. When you do projects for like practicing and developing your skills, you don't really put in the effort to make sure they're super polished, making sure the storytelling is like, you know, up to par or whatever. I want to show the differences between the two. We are going to be doing projects for showcasing on our portfolios. And the idea about your portfolios is that these are going to be 3 really high-polished projects that you spend a good amount of time on them once, and then they compound as far as like do work for you like afterwards. Like you don't have to put in the same amount of effort every single time. Again, you could use ChatGPT, you can use Claude, Perplexity, you can use Gemini. We're going to use Manus today, which is another AI tool, and we are going to ask Manus to basically fish us a high-value project And also the dataset. So I'm going to say I am an aspiring data analyst. I want to build a portfolio project on a high-value problem in my target domain being supply chain. Can you find me real data? Sets online and build a CSV on— I thought maybe ACES, but build some CSV files or file, you know, for my data analysis project that I can do in, you know, Excel or Tableau. So the great thing about Mantis is that it has like inherent agentic Abilities in there. So what I'm going to do is press send and just see what happens. Asking me, hey, focus areas. You know, supply chain is broad. Do I have a preference or should I pick the highest impact one? Right. That's a good question. Inventory management, demand forecasting, supplier performance, logistics analysis. So what I'll say is I want descriptive analysis, but you can decide the rest. And again, you can always say whatever you want, but those are really good. So that's another thing with Kaggle. Sometimes there's a lot of datasets that's really like designed for like data science predictive stuff that's not very good for, you know, descriptive stuff. So that's a very good question. Avoid Kaggle, right? That's one thing I love about Manus. You can QA the AI in real time because it's saying exactly where it's finding the sources and things like that. So it says it's found a dataset from the Brunel University and then something from data.gov. So those are real good. Anything from data.gov is a good chance it's going to be some You know, data cleaning. So when you do something that's not Kaggle, it found some stuff for us, and it's gonna be nice to see what this looks like when it's done. No, do not clean it. Do not clean these. So I did say— so again, when it comes on to QAing the AI, it was saying that it was going to clean it up because I had said that, hey, I want to do some analysis in Excel and Tableau. So it took it upon itself to say, hey, let me go above and beyond and clean it. And I say, nope, nope, nope, don't clean it. We want this run authentic so that, you know, that's stuff that we could do, you know, for our project. And then it could even give us a project brief, which is pretty cool. So it gives us a project brief and then it gives us a zip file of all of our data. So we have 1, 2, 3, 4, 5, 6, 7 datasets. So look at that. So this is even stuff that honestly you can also take into SQL and do some joins and stuff. Again, way better than just doing some stuff on like, say, like Kaggle or whatever. Okay, so I'm going to make a new folder and say, you know, supply chain. All right, so let's start the folder, create the folder, and then extract. And so cool thing is that Even made a project brief in Markdown. I'm gonna go back to Manus and tell it to export the project brief in Word doc. One thing that I love about Manus is that you can QA, quality assurance, the AI in real time. You see the steps and say what it's doing. The project brief being in a Markdown file, so just ask it to export in a Word doc so I can just look at it. Easier. We'll see what this project brief looks like. You know, it's pretty much on you if you'd want there to be a project brief. If you want to look through the data first, it should be exporting the brief. Let's look at the project brief. So we have 1, 2, 3, 4, 7 datasets that's interconnected. It gives us some suggestive descriptive analysis angles. So even before looking at it, it gives us some suggestions and angles that we can look at. So I haven't looked at it yet. We can look at order fulfillment for on-time delivery. Transit time is giving us questions that we could do, capacity warehouse utilization and things like that. So this is really good. So again, this is a dataset looks like they got from a university. And let's actually just look at what we have so far. So we've got freight rates. Okay, so we have stuff like this. We have order lists. We have state order IDs. Unit quantities, whether it was shipped late or not, costs. So again, for the sake of like an actual project, like this is really good stuff. Like it's multiple CSV files. You can use AI to help give us an idea of what's going on, an idea of just getting started. Again, we can look at through all of these CSV files and just do some good analysis for a project. So this is good stuff. This is way better than something that you find on Kaggle. Okay, we can do this. You can literally do the same sort of prompt for whatever high, you know, domain you want to do. If you're not sure which domain you want to do, yeah, like you can kind of take the MBA approach, right? An MBA, for your MBA, all you have to learn about all areas of like general business, right? Finance, marketing, accounting, strategy. You can kind of take that approach and then do things like, you know, do something like into product, do a prompt to find a dataset relative to marketing. I do a prompt to find a dataset relative to healthcare analytics. And again, I love Manus. I recommend Manus because it is— it has some agentic features in there where you can actually QA the AI in real time. As you can see, there was times where I would see that, hey, it's cleaning something or it's doing Kaggle, find me something with Kaggle. And I'm like, you know, you can message it and talk to it in real time, be like, hey, nope, don't do that, you can divert something else. So for the sake of the video, what I'm going to do actually, um, there will be a link in the description to this dataset and also the project brief along with some other ones I'm going to make as well. It's going to be like a package of like a, you know, portfolio challenge where you guys can, you know, do these high-value projects that are, you know, with real data that's sourced not from Kaggle. Let me know in the chat if you'd like a, you know, Madness for Data Analytics video tutorial. If so, Like I said, I love using Manus. I use Manus all the time. And I do think that, you know, the AI-powered data analyst, the AI-powered full-stack data analyst is the new thing that everyone has to do. So let me know in the chat if you want a Manus for data analytics, AI for data analytics, like tutorial series. We'll go from there. There's tons of resources on how to do these tutorial projects, like step by step, like, hey, watch me do this project end to end. There's a bunch of end-to-end projects that people can follow. How many people have taken courses? Everyone raises their hand. But how many people have, you know, done projects? Everyone raises their hand. But how many people have a portfolio? Very few people have an actual portfolio. And the thing is, when it comes down to landing a data analyst job today and in the future, especially this new AI job era, you have to think of a portfolio just like your resume. Like, everyone has a resume, or they know that they should have a resume. You should think of the portfolio as like top of the line as your resume. Like, everyone should have a great LinkedIn, everyone should have a resume, and everyone should have a portfolio in this job market. All right. So for the sake of this video, we're going to do is I'm actually going to build out the actual portfolio with completed projects that my students have made based off of things that, projects that I designed for my program. But what we're going to do is we're going to first pick out a portfolio website. So I love Canvas. I mean, Canvas. I love Canva. They have tons of portfolio websites. So if you go to templates and then let's say we go to website and portfolio, website portfolio is a good one. Again, there are tons and tons of, you know, templates that you can use and it's very, they're very easy to edit, manipulate. There's tons of them, right? And it's easy to just go in and edit. So what we're going to do is we're going to use a template that I already designed. I actually combined a couple of them. Into one. It's like a combination of this one and some other ones. So we're going to start with that template. Let's see, this portfolio template. And I'm going to also have this template. So this is the link of it. I'm also going to have the link available. This is a template. Let's see, view template. Open in editor. It's opened as me. So what I'm going to do is I'm going to make a copy of it. All right, then we're going to call this, uh, Dem Portfolio Template, Dem One Pager Template. YouTube. Okay. And I'm going to show you how easy it is to edit a portfolio template on Canva versus say like another website. Even if you vibe code, I would not vibe code, do any of those vibe coding sites for them. Again, when it comes down to portfolios, there's really 4 E's. You want it easy to access for people to look at, easy to navigate. One-pager portfolios do that. Easy to consume, right? One-pager portfolios do that. And for you, you want it easy to maintain. So we're going to show like how easy it is to just copy and paste and add these text boxes versus, you know, working with code. This is an actual, my actual portfolio site that's not as updated, but this has a combination of like about me, has a combination of like a bit of my resume at the time. And then some actual projects that I did in the past. The thing about portfolio projects, you know, we were actually putting in projects that you actually spent time on. Honestly, this is something that I did, this email marketing project, I did this project in 2021. This marketing plan project I did in 2020. Yeah, 2023. And I can still, if you ask me about these projects, I can still walk you through them like I did them yesterday because I actually did them. And I spent like way more time on these projects building the deck than like the projects for practicing that I mentioned, right? Because you want to put in an extra amount to make it polished and things like that. So one of the reasons why Why I mentioned this is because when I was learning and doing these like projects, when I was taking courses that had like, oh, hey, these done for you kind of like tutorial projects that you could just do step by step. And then just like, you know, hey, just put them on your portfolio. I would do these projects, you know, do the step-by-step tutorial projects. And then the next day, I wouldn't even know what the heck I just did. Right. So I felt like a fraud having these projects on my portfolio that I couldn't even talk to you about it. So that's why you want to avoid doing that. Let's remake this right now. And Let me pull up the portfolio projects that we're going to actually use for the project. So let's see, this is a project. Okay, so we're going to have something. So this is a milestone project in my program that one of my students did. So this was done in Excel. So we're going to do something with Excel. We're also going to have a— we're also going to have this. This is a project for our internship. We're also going to have a Tableau dashboard. And we're also going to include, we're also going to be including an executive consulting slide deck, right? So we're going to have like those like 3 versions in our portfolio, design in our portfolio. All right. So you want to have a picture, right? So I'm going to keep my picture there. Want to have an about me. So again, this, this Very first, when you're designing your portfolio, you definitely want to have a picture, definitely have your name, and then you want to have links. Consider this like your first impression, just like on your LinkedIn, right? On your LinkedIn page, as soon as people open to your LinkedIn page, you have your banner, your photo, your headline. For your portfolio, same thing. And your About Me is basically like your elevator pitch and then like your list of skills. But one thing that you can do with Canva, it's easy to create text boxes for links. So like, say for example, let's say I wanted to create a text box To create, I don't know, you know, to a Tableau Public page or something, right? So you do Tableau Public. That's a great thing that I love about just create a text box, you know, Tableau Public, Tableau Portfolio, for example. And then what you can do is you can double-click and then click this link, and then you can just literally Paste in the link to your Tableau Public profile. Let me see if I can find my old Tableau Public profile author, and here I am. This is the very first Tableau dashboard that I did. As you can see, this was first published September 18th, 2021. It's the very first public one, I would say. I think the very, very, very first one that I had, I must have deleted it because I thought it was ugly. You can kind of see the progression over time. So that's the great thing about Tableau. You can just kind of go back and see. Let's say, for example, I'm just going to copy or duplicate this and I can do a duplicate of and say like Tableau Public, Tableau Public Portfolio. And when I double-click, I click the edit link and I just paste in the, and then yeah. And so my LinkedIn profile, you definitely want to have a link for your email. Your resume, and for your resume, what you want to do is you want to upload your resume to a Google Drive, and then you want to make sure that Google Drive link upload is like accessible to everybody. And then here you just paste in the link to that Google Drive of your resume. And then same thing for your LinkedIn profile. You want to have a link for someone to email you directly, PDF of your resume, a link to your LinkedIn. And you don't have to have the Tableau public. You can just have it there if you want, but you don't have to have it. Just did that there so y'all, y'all can see how easy it is to use this template and create an actual, you know, the links. All right. But as you can see, no code so far. So when it comes down to that, all right. So that's that there on the right side. Again, your About Me and then your Skills. Your About Me is basically your elevator pitch. Everyone should have an elevator pitch, right? You should always be ready whenever you're ready for applying for roles, right? If you think about it, you build your skills, you build your brand, then you build your story. You work on crafting your story, uh, and then create your experience. Once you're applying for roles or whatever, you never know when, you know, an opportunity can come. You don't know who you're speaking to, and you always want to present yourself well online. So your About Me, it's literally like just a few sentences of like a version of your elevator pitch, right? So this is an old one that I have, but I'm just going to keep there. For your skills, the way I like to design, you know, have this set up is like left side, I have like left side for like, say like harder skills. And then when I have like your right side for like your soft skills. So left side I had at the times like SQL, data viz, data storytelling. I don't know why I have data viz twice. I can do Python, Tableau, you know, machine learning. On the right side, you know, very strong soft skills, not just soft skills, but strong soft skills. So problem solving, creative thinking, Six Sigma, something that I have a green belt in Six Sigma, process improvement, leadership, community building, right? Not team player, not great listener. Okay. None of that stuff. Actual strong soft skills. And when it comes down to today, problem solving, creative thinking, leadership. If you have those things, you better highlight them and put them like top 3. Those are things that folks really want, and those are things that are degrading by the second with AI today. Okay. So this next section, this is a, this section is optional. This is a section where if you want to kind of like intertwine your resume in here. So this is quite old. I already graduated, but just going to put that there for now. You know, you could have your degrees here if you have certifications and then just like your, literally like your resume here, but just kind of like brief. And then it goes on to the projects. So let's redo these. Actually, what I'm going to do is I'm going to just make kind of like new ones fresh. So what I'm going to do is I'm actually going to delete and we're going to make some new pages. We're going to make some new pages. We're going to add a page. We're just going to delete and kind of start fresh here. So let's start with our first project that we're going to use. We're going to use this Excel project. All right. So this has, you know, this person has some visuals here. This project was about analytics about college majors, like graduation for, you know, employment, unemployment, stuff like that. Also salaries. So what we're going to do is we're just going to take some of these, maybe like the strongest, what we find is like the best visuals that we would like, and add it to our— and show how to like, you know, add it to convert, you know, these into a portfolio. So as you can see The project that we had, it had over like, it had like 13 questions. We're not going to put like 13 visuals. We just want to pick like the strongest ones. So like for this, this is, this is interesting. So it's a stacked bar chart. So whatever it is. So let's say we can just pick, I'm just going to take a recommendations. I'm going to start with. A text box that's like a kind of like almost like an action title, sort of that kind of describes the project. We're going to do you know college college major employment and earnings analysis for I'm just going to do analysis and let's see keep it bold. All right, so this is a question that pretty much compared if there was going to be a relationship. Between like the popularity of a major and employment rates. And by this picture, we could say no. This was one where, you know, the most popular majors were psychology, communications, biology, and then the graduates with full-time employment, you know, not as high. And this is pretty important, especially now when it comes down to if anyone's seen there's colleges around the country in the US that are actually removing majors, you know, a lot of the liberal arts majors that are not, you know, really panning out for like employment, employability, and earnings for people, you know, since you graduate. All right. So this is Excel. So what I'm going to do is I'm just going to copy. I'm going to copy this, come back here, and I'm just going to paste. Simple as that. And then we have our visual here. And so we can do that college major there. And then let's see if we want to get another or some other visuals that are pretty good. Interesting. Medium income from women-dominated majors. 33. That's interesting. And let's do this one too. Top 5 majors have at least, you know, 44% female graduates. Psychology has the highest percentage of female graduates. It's interesting. All right. All right. So let's see what else I would like from this project. Psychology is the most popular major. Okay, so for the sake of the design of the page, what I'm going to do is I'm going to replace and just have like 2 kind of square photos here. And what I'm going to do is just have like a blurb of each, a small blurb. So you can do multiple things. So these, we teach our students to do action titles for the project. So since these already have, you know, kind of descriptions or action titles for each chart, What you can do is have like, you know, title here and then have like a blurb describing like the project itself. So here I'm just going to take what maybe some of the recommendations, or just take some of these recommendations and have them in here. Move that over. All right. College major employment earnings analysis. This project, you know, analyzed, you know, it could be whatever amount of rows, whatever, you know, it could be analyze, you know, 20,000 rows of data covering, you know, college, covering, you know, employment and earnings outcomes for college majors. Recommendations include, and then here I'm just going to paste some of the recommendations. In creating internship opportunities, creating internship opportunities for field, and I could add one more just for the sake of it. I'm going to say it could include also mentorship programs. That's a good one that I like, and mentorship programs. All right, so here basically title, small like blurb of the project. Here I also included the Recommendations of the project, and then just a couple visuals. All right, so what I'm going to do is I'm going to copy or duplicate this page, and then we're going to add our next project. All right, so that was Excel. The next one is going to be just a plain Tableau one, so a dashboard. All right, so this is going to be the dashboard. Let's see, there's 2 things you can do. You could export The PNG, you can export the PNG with Tableau. Now, if you go to this top right, you can say download and download image. I will say for whatever reason, a lot of times when you when you do that, it looks weird for whatever reason. So I actually I just recommend honestly taking a snippet of it. So my screen up above me is actually bigger with it on top of the screen above me. Copy, and then let's remove. All you do in Canva is click backspace, and then right. So like that's gonna be way better. So now I literally just copied and pasted it, or took a snippet from the website on Tableau. This is employee attrition analysis. I'm going to just copy and paste what we have here. So again, a lot of the work whenever you're making your portfolio is already done. All right, just so it fits or it's. Okay. And I think we can just make, let's make this 30 and also make this 30. Okay. All right. Employee attrition analysis, identifying key drivers of turnover. All right. And so here what you can do is I can just do a visual or a kind of overview. So with this, we have 11.9%. And you can say here, you know, analyzed, you know, analyzed. Employee. Actually, this is actually healthcare. This is actually in health, which is actually, I don't know, in healthcare. If you're into like people analytics, again, this goes into the, the 3 Rs retention. And this actually covered a healthcare type of thing. So employee attrition analysis in healthcare. So like here we did college major employment. So this is like education. So just highlighting the industry or the domain. And this one is we're going to do employee attrition analysis. Let's see, key drivers of turnover. And I can just do that. Most of the work when it comes down to building a portfolio, most of the work is all in the project already. As long as you, it's all about just knowing what you're doing and can be able to explain and defend your project. So I'm just writing these out by hand. Some of you guys can use AI to help you create like a bit of a brief and things like that. It's fine. Just make sure that again, you can defend these projects if asked about it. Just the other day, we actually had a student. Who landed a job, a 6-figure job, and he actually showed his portfolio that he built in the program, same Canva thing, and he showed it inside during the interview, like walked through the portfolio projects in front of the VP and he got the job. So when it comes down to this portfolio, before you get the interview, before to get the interview, and you can utilize it as an asset to showcase During the interview, that right there is that's a secret sauce. All right, so they analyzed attrition of over 1,600 employees in healthcare and found discovering no it could be discovering an 11.9% attrition rate with an average salary of 78k. I don't know, seems kind of low for healthcare. I'm just guessing. With the highest turnover, you know, department being cardiology and maternity. All right. So I can say something like that, like a little blurb. And then what I could do is I can highlight, utilize color and just highlight this attrition rate and say, make that bold and make that blue. And then also do the same thing here. Average salary of $78K. How to bold these? Bold blue. Okay, on this dashboard we have one, two, we have six visuals, and most likely there were there's probably going to be twice as many visuals that you did during the project. What you can do is also paste in some other visuals that you did for your analysis. Let's say like did not make the dashboard. Just for the sake, what I'm going to do is I'm going to take. But I feel like the most important ones and lower satisfaction equals higher attrition. That's really cool. Actually, I see what frontline roles have higher attrition. You can see like nurse has like higher attrition than admin, which is like zero. So I'm going to do, I'm going to just literally just copy and paste. I'm just going to copy and paste and I'm just going to do it for another one. Lower salary, higher attrition. So just going to copy. So for these, for like for a Tableau project, highly encourage you guys to have basically on one side a photo of the dashboard. Sometimes you— the dashboard can, can take over the entire page if you'd like. And then some visuals that did not make the analysis but, but also supports. All right, so we got this. All right, and then we're gonna do one more. This one is going to be one with a dashboard plus our slide deck. Let's see, so this is going to be the dashboard. This, this is a dashboard project for our internship actually. So I'm going to copy this straight from Tableau again. Again, you can export as a PNG as an image, but I, for whatever reason, a lot of times the export from Tableau is weird. So I'm just going to take a snippet and paste it in here. As we can see from this one, this one actually takes a big chunk. Of the page. So what I'm going to do is going to have one page just for this dashboard. And what I'm going to do is I'm going to let's say there's actually multiple pages of the dashboard. What I'm going to do is I'm going to change the title. We can call this you know marketing analytics dashboard marketing analytics for growth marketing analytics for Let's see, growth, startup growth. Analyze, you know, marketing data covering social media, paid ads, look, operations and sales to cover process improvements and identified gaps. So This is a gap analysis, identified gaps to help, you know, unlock 25% more revenue opportunities, stuff like that. And identify, okay, so you have one page just for this dashboard here. And then what we're going to do is we're going to duplicate. And what we can do is I'm going to find Jordan's slide deck. So this is Jordan's slide deck here. What we're going to do is we're going to copy some of these. It depends on whatever. It's the same project, so we can do— so this covers like some of the data that we had that, um, this is a good one. I'm going to copy this and then I'm going to paste it here. And then I'm also going to pick— let's see, I'm also going to pick— so this talks about YouTube being the largest driver, 40% of book calls. So that's really good. We're just going to pick ones that show some good benchmarking. So this one is good too. This one gives a good insight on the non-cleanliness of the data, which is really good. Really depends on honestly the type of, you know, the story that you want to provide. So for example, this is good. So this one highlights unclean data. You know, identifying that you know the data isn't that clean. So that's actually really good. Say like identified. I'm going to duplicate, and then we're going to do some blurbs here. Okay, so identified that YouTube provides the largest source of booked calls and revenue generation. And so here, almost 40%. So that's really good in here. And then again, we can do a bold. And then for this, we can do a blurb of just copy that and just do a blurb of identified a data quality concern, identified a data quality concern of over 30% of calls, calls have No attribution source, which or say which calls for you know a data quality intervention. You know, data quality intervention. Okay, so that's concern over thirty. And when I remove this, and I'm just gonna put this up here. Or it's gonna move up there. Okay, so let's look. We can actually see what we have so far. So what I'm gonna do, we can do preview, and this is. What the website would look like so far, which is cool. We have Excel, we have Tableau. Okay, this could be Power BI if you'd like. And then we also have a dashboard, another dashboard, and slide decks. And then we see how we can easily use Canva to just copy and paste and whatnot. So what I'm going to do now is I'm going to just show you how easy it is to just publish the site. So here, uh, what Canva does, it gives us our own website, it hosts it for us, and we don't need to pay for nothing. So what I'm gonna do, I'm gonna do publish and then I'm gonna show you how easy it is to have that. So our website is live. So this is an actual URL, one that I'm gonna have in the description where it literally shows. So this is something I can link to my resume. I can link it on my, my LinkedIn and look how easy it is to just scroll down to just to see stuff. It passes the whole test. Easy to access URL, easy to navigate, one pager, easy to consume. It's easy to update, right? We saw that easy to maintain. It's just copy and pasting, right? So I'm going to have this linked in the description. The template is going to be in the description. The, this finished portfolio is going to be in the description. And also I'm going to have a data portfolio analyst portfolio challenge with the supply chain dataset and also a couple others that you guys can do.