Right. If we're almost settled, perfect. All right, good to see you all. Welcome back. Let's get the recorder and we'll get moving. All right, everybody, welcome. My name is Phalas Dupaglesi from Cybertrain University and before I get started, happy Passover, happy Easter if anyone's celebrating. We've got a couple of things going on the market. We got a little bit down. It started coming up a little bit. We're gonna talk about some stocks that are moving very well, but our main goal is not teaching you how to find them but how to stop losing them. So we're gonna talk about how to look at real-time orders and analyze in today's stock market. Now, I'll ask a couple of questions.  We're gonna simulate a little bit here.  It's gonna go fast because you're gonna start seeing things that are gonna make sense and that you're gonna get so into it. But the key about today's event is that you have to ask questions. That is the most important thing. The more you ask questions, the more we learn, the better it is. Now, first of all, like I said, markets gonna be closed tomorrow. For some of you don't know that due to the holidays and I guess I just wanna wish everyone a happy Easter and happy Passover in the meantime, okay? Now, before we move on, a quick little risk disclosure. We do have some instructors in here. I see a mod, you just ask a question and anything like that. So anything that questions that will be answered, like I said, I can't stop and ask all of the answer, all of them, but I will at the end, they'll be happy to answer them for you. But just quick little disclosure, just to let you know this is strictly just educational purposes. I'm not making any guarantees or warranties. This is all strictly teaching you how the market works and hopefully you'll take with a grain of salt and move on with us. Now, this is a couple of things we're gonna learn, all right? We're gonna talk about best stocks to trade today's markets. We're gonna talk about navigating the challenges of the high-frequency trade, the algorithms. We're gonna talk about something that is called level three or level four, which some of you probably are stuck on just on level one quotes. So we're gonna show you how that works, entries and exits and how market makers and meaning brokerage firms, how they do tricks and traps in the trade, how you get suckered into trades, how do you get out of them, all that good stuff. Now, with that, let me just tell you a little bit about Cybertree University and we'll get right into it, okay? So I founded this company over 30 years ago and we're one of the first educational schools in today's industry. We got a five-star rating on Google over 30 years. We're endorsed by every brokerage firm. NASDAQ's one of them, Trade Station, Thinkorswim and the purposes is that, you know, I'm a market maker, I started on Wall Street and what happened with me was I didn't like split my profits after a while. So the only way I can continue is I had to educate and educate people like you and my goal today is this. I wanna educate and show everyone how and why a lot of you are trading backwards. So at the end of this presentation, I'm gonna hopefully get all of you to come and see it live in the market. So you can see, touch and feel and see if all the traders make money because that's the key.  If you don't like what we have to teach or explain what we are style, there's no reason to continue but we'll see how that goes when we get started getting to a couple more slides. So that's how I got started.  I was one of those kids and the funny part about that photo is those old monitors we used to trade on but the thing is a lot of you are trading backwards. You keep going out there and you look at the past, you not look at the future. Jeannie, yes, I was one of the prop trader. I was a prop trader. That's basically what I did back in the old days but in today's times, you don't have to do that anymore, okay? All right, so I have two families I wanna share with you. You can see I have my lovely wife, Debbie. I got my three boys, Alex, Max and Lucas and I have my second family. And here at CyberTrain University, we don't teach the masses, all right? We don't have full 5,000 people in my room. If I want to, I could but that doesn't help you. So don't take this with a grain of soul. A lot of you really don't qualify to trade, okay? But hopefully after today, we'll see if that's gonna really be something you wanna do and we'll hopefully if everything works out, maybe you'll be part of our family, you know, here at CyberTrain University because we trade like a team. So if you're a team player, that's what it's all about. So why are we here? Okay, that's really the ultimate goal and everyone's gonna probably agree it's to make money, all right, but that is absolutely false. You are not here to make money. You are here to stop losing it. That's what everyone's issue is. Everyone likes to talk about winners. Everybody likes to talk about, hey, look what I trade. Hey, look at this stock.  That's telling me how much better I am than you. Do you really want that? How could you actually be that good at it? You know, the goal is you wanna make sure you don't make those mistakes. Someone has to be the adult in the room, right? And you wanna have children, you don't just let your kids go run wild because you know where they'll end up being. Okay, just let somebody drive a car without teaching them how to drive. That's what it's all about and that's why you have to learn before you could earn. So let's talk about a couple of stocks that are moving because they're actually moving again today. Did anybody here trade any of the AI stocks? They're moving great today, by the way. You hear so much about them. That's just a specific industry that just kind of caught some wind in the market the last couple of days. Nobody here traded it. Charles, you never traded it. Dan, Dex, I see a bunch of people. Dan, now we're starting to get people chatting back. Listen, this is a live webinar. This is not some of these fake recordings, okay, everybody? So just listen, I'm gonna ask questions and then quiz you and all that. All right, so you could see how these stocks made some big, big moves, all right? Big, big pops, you know, GFAI, by the way, that stock moved unbelievable today too. This is actually that, that was actually a couple of days ago. This is actually this morning, okay? The stock, you can see what it did this morning. Look at what happened. Stock went from $9 this morning, $9 in less than an hour. It went to 14. AI went from $20 this morning to $10.30 to almost $23. These are the things that you have to look at. Now, your question is this. How do we find them, which is Kathleen, what you're asking? And most importantly, why did they go up?  Why did these stocks go up? What made them go higher? Let's see how some of you answered this question. Mara, okay, you're right. Hie, you're right, okay. Jenny, you're right. Bitt, Larry, you're right. Oh, so you're telling me, all right, now for the ones I'm not answering. So you're telling me it's not because of a moving average, a bolager band, an RSI, what else is that? Pretty cool. Oh, a MACD, right? So you're telling me it has nothing to do with this. It was all about buyers and sellers. Well, congratulations, you are 1,000% correct. And that's what we're gonna talk about.  And the source is what's driving them up? The KISS method, keep it super simple and then obviously following the orders. So big thing about trading is, I don't know about what kind of trader you are, but I'm an actual day trader. I don't know if any of you ever met one, but I am one of the original source traders back in the early 90s. I know one of you just mentioned earlier about prop trading. That's basically what we do here on Wall Street. Now, some of you be like, ooh, I don't want day trader, that's scary. I mean, it's risky. No, it's actually the least risky. You know what's risky? Options. You know what's risky? Swing trading. Because if you hold an overnight position, these things can get crushed. See, because what happened in AI, look what ends up happening. You hold for a couple of days, it goes from 34 down to 21, all right? That's where you get yourself in trouble. GFAI, great run up, look what happened. It goes from 22 down to nine, like that.  And how you've known if it was gonna continue to go up, like when most of you said, buying the buyers.  Follow the sellers. That's how you trade in today's market. Now, listen, that's just the flavor of last week and this week. Every week it changes. The week before that, what was it before that? The stocks, remember? All those bank stocks, what was it? Wall and Key Bank and, you know, Paco West and what was the other one? Republic Bank, all the California stocks, right? It's always a new adventure every day, but you just gotta know what's driving them up and what drives them down. And that's how you become a good trader because let me explain something to you. You don't need a lot of money to do this to make it a very successful career. Now, one of you asked a very valuable question and you say, okay, how can I find these trades? And believe me, it's not as hard as you think. You wanna know what my crystal bowl is? The big percentage gainers and losers. How many of you here have a big percentage in gainers and losers? Anybody here have it? Some of you are like, well, you know, so many stocks, I don't know what you wanna carry. Miranda, you have it, okay, good. Jenny, you have it, good, good.  You know what you do care? You should care about risking the least amount of money as possible with the high amount of reward. That's what it comes down to it. So when you come into my trading room, all these stocks that you see right here, I'm gonna show you how to find them and which one is gonna be the least risky that if you're on the wrong side is gonna give you the less harm. Because all of them are doing well, it's just which one is moving. Now, does anybody have an alert system? Anybody use any alert systems? Okay, well, let me tell you what my alert system is going to be. When you come into my trading room, we have a Twitter feed, a YouTube feed, Instagram, an alert service. So everybody here, if you wanna be able to monitor and see what we get in and out of it, we're gonna give you access for free, okay? Why? Because you know what? Everyone wants to charge something, right? But to me, I'm like, listen, you need to do your homework. You need to see like, is this guy really for real? And does he know what he's talking about? And does these things really move? Because that's where it comes down to it. Listen, I've been doing this for 30 years, okay? And trading is about a 90% failure rate. You're actually doing yourself a disservice to get into this industry.    Did anyone tell you when the best times and the worst times to trade? Did anybody tell you which brokerage firms won one stock versus another?   These are the things that are gonna make things differently. Does this training have any? No, we don't give certifications. I don't know why you keep asking that question, Amad. We don't give certifications when it comes to trading, okay? If you wanna do that, you go to Harvard, dish out about 300,000, all right? Okay, so the thing is this, indicators, everything else, you know? The big thing is we're gonna follow the big order. So now what we're gonna do is we're gonna get into the education part of it. I'm gonna show you what makes these stocks go up and go down the way they do. Now, the biggest thing you have to understand is this. You got level three quotes and you got level four quotes. I'm gonna talk about that. When you started to see level three, you guys are gonna follow up your stocks. When you see level four, that's when you follow up your chair and you're gonna be like, and by the way, get your phone ready. Get your phone ready right soon because in another couple of minutes, I'm gonna tell you how to scan something with your camera to get into the trading room, all right? Let's start off with something called NASDAQ Book Viewer. Now, this is on the NASDAQ exchange. I was actually there yesterday. We were talking, I was talking to the developers about redesigning and this is how NASDAQ does their trades. Does anybody here have NASDAQ Book Viewer? That's gonna be my first question. Actually, do I have a poll that I could do here? Let me see, I got a poll. I love doing polls. Okay, yeah, I do. Here we go. There's a poll. All right, let me launch a poll right here. Does anybody have NASDAQ Book Viewer? Just give me a yes or no in that. It's only, I don't wanna go over the pricing right now, but let me just see how some of you answered this question. All right. So with that said, let's think about this for a second. What you're about to see is where probably more than 50% of the volume is being taking place right now. Think about 50% of the orders that go on in today's market, you're gonna see it. Basically, you have a seat on the exchange, all right? Now, when I started to buy seat on exchange costed a couple of million dollars. You want to cost today? $15. Now, is anybody here willing to buy a seat on the exchange for 15 bucks? Anybody here want to pay $15 for it? You have a seat on the exchange. I mean, you can see all the buyers, all the sellers, all that stuff. All right, first of all, let me put it this way. Let me share the results. Look how many of you do not have Book Viewer. So let me just put it in perspective because I don't want to waste your time and I don't want to waste my staff time. If you don't want to spend $15 that we paid millions of dollars back in the past, back in the 90s and 2000. If you don't want to spend $15 on have a seat on the exchange, do yourself a favor right now. Start interviewing stockbrokers and get out of the trading business. Just get out of the trading business. You are wasting your time, okay? Why would you not want to have a seat on the exchange? Now, the NASDAQ has given you that access. What more do you need to see, all right? And I'll tell you where to get it. But before we do that, let me explain to you why it's so valuable, okay? So over here, let me get my crayons really quick. Where's my crayons? There you go, okay. So here are your buyers and here are your sellers. So what you're seeing is every buyer and every seller. Now whoever wants to buy the stock for the most amount of money is up on top. Whoever wants to buy for less money is down at the bottom. Same thing for the sell side. Whoever wants to sell their stock is up on top. Whoever wants to sell for more money is at the bottom. This is the price they want to buy for it. This is the amount of shares they want to buy and this is how many orders make up those shares. So you are seeing every single buyer around the entire world that are looking to trade AI right now. Is that amazing? Like think about that is phenomenal. How could you not see that, right? So let me clear this out and let me move on and show you a little bit more. How do we utilize this data, okay? So let's think about this for a second. AI came all the way down and it stopped right here around 24, 50s. Everybody see that? Okay, why did it stop at this price right here and decided to go up? Because it's not because of Fibonacci said so. It wasn't because of MACD said so. It's not because of your program trading said so. It was because on the exchange, on the NASDAQ when you get down to 24, 50, there was 33,000 shares looking to be bought at that price. Now there are buyers at every single price, right? 200, 400, but when you got down to 24, 50, that's where you had probably about, was that 30, 40 times the average order out there at that price. Now remember what you said earlier? How does stocks whoop and go down? Buyers and sellers. You are now officially seeing the buyers and you are now officially seeing the sellers on the exchange. Now how much smarter and better trading decisions would you make by seeing those orders? I think you'd probably do a lot better, okay? Now let's move on and look at another example. A couple of questions coming across here. How does it show only passive buyers and sellers or aggressive ones? Well, we didn't get there yet. How about that, okay? Is it $15 for all stocks or just crypto? We're not talking crypto, Jenny. This is specifically just stock trading, okay? Now let's look at, let's look why a stock would go down. So here's a stock, ENVX, it goes from a price of 12.70, shoots up to 13.50 and you could see it at 12, 12.30. Never wanted to break this price of 13.50 and then finally it comes down. You ever want to stock in like, then why is it going down now? How did I not see that? Well, if you looked over here on the sell side on the NASDAQ exchange, you will notice you'll have a 43,000 share seller out there. Kind of makes sense, I mean, because I don't think a 400 share seller is gonna push it down, maybe not even a 1600, but when you look at all those orders and you see that you're coming up to something that is almost 30, 40, 50 times more of the average orders out there at a specific price at 13.50. Yeah, I think it's gonna go down, okay? Because like what we said, how do stocks go up and go down? Buyers and sellers. Guess what fellow traders, what are you seeing now? Buyers and sellers. Did I lose anybody? Did I lose anybody yet? Just give me a yes or no. Just wanna make sure I'm following along. Okay, well, you know what? I'm a little insulted. I'm a little insulted, okay? I'm gonna tell you why. We've got almost 100 people in here, all right? And Keith, I didn't hear from you. Michael, I didn't hear from you. Snapper, I didn't hear from you. Why are you guys not answering? I mean like, listen, do you wanna learn and understand something? Listen, don't take it in the wrong way. Thank you very much, Wolfgang. I appreciate it. I wanna make sure you guys are listening because I'm not here for my health. I'm here to help you. You know, I've been doing this for so many years and that I do so much public speaking that when I look at an audience and I look at all your faces and here you are just starving for education. I mean, you made the time to show up here. So did I. Answer the question. You know what the best thing that could happen? You answer it wrong. And I would be the one and my staff would be the one to tell you, hey, you did it wrong. That's all. No problem. Snapper's listening. Snapper, good job. All right. Let's talk about stocks that love taking a fall. You have your own a stock and it's tanking and like, what do I do? I'm like, do I take the loss now? Do I sell it? And sometimes you ride the stock so low that you can't even afford to even take a loss. Well, the goal is this. What makes a stock stop? Buyers. Let's look at this AI trade. You know, listen, it's up, it's down, it's going all over the place, but the goal is what stops it from going up and going down? Buyers. And when you look over here, without even looking at history or past or anything else, you'll notice that right here, you got a buyer at 2134. So what do you think happens when you got to 2134? Boom, the stock goes up. Jenny, we're going to talk about level four in the next few minutes, okay? Because I know you keep asking that question. We didn't get there yet. All right, that's the second part we're going to talk about next. Right now, my goal, Jenny, and everyone that's here is that some people don't even notice even exists, okay?  I was at NASDAQ yesterday, okay? I'm, you know, I am one of their speakers. By the way, if you go to, let me just show you something. If you go to our website, let me bring this up and show you. If you go on our website right here, you can watch videos. Like I'm actually one of their experts that come in and teach you this stuff. You know what they said to me yesterday? They're like, Fausto, I don't know if we could really continue with this book viewer, because a lot of people are not even looking at it. And I just don't understand why no one would want to use this, have a seat on the exchange. And you know what their argument is? Their argument is that the people that are buying it are the brokerage firms, but people like you are not. And you know what I told them? Is because you people are not educated enough to know the value of it, not enough people are talking about it. But here now you're starting to listen in like, my God, how do I not have this? I mean, that's all it costs. Why would I not have a seat on the exchange? So the thing is when you're starting to look at stocks and want to know why they bounce off support or when to take a resistance level on Oscar and knowing that you're coming up to a 54,000 share seller and a 17,000 share seller with 17 different orders around the world, hopefully that explains it. Because if you don't have that game plan, that's how you end up taking big losses. Now, these are what we call iceberg orders. I came up with that word over after watching the movie Titanic, okay?  I'm actually gonna tell you how to get it right from NASDAQ, okay? Do I have it up here? No, I don't, okay. So let me give you the link. I thought I had the link up there and I don't know why we took it down. But it's, let me give you the link, okay? So here's the website right here. This is the NASDAQ's website. So everyone just click on this link right here. And basically this is how you subscribe to it. You could see it's $15. I don't think anyone here is professional.  But right there is 15, that's how you get it, okay? All right. So let's talk about a couple of other things, all right? Now, some people always ask me about are they fake orders? How do you know they're real? Whatever it is. Listen, if you think they're fake, when I invite you into my trading room, I'll find some of these orders and we'll use your money.  I always love to say that. I say in every webinar and hopefully you'll see what I mean. Now let's talk about something called level four, okay? Now if you thought level three was pretty cool, wait to see level four. So this is basically level three right here, okay? Oops, right here. This is level three, right here. And this is level four. So here's your three and here's your four, all right? Now three you could see is a lot of numbers. So kind of sometimes some of us get a little confused. They say it moves too fast, whatever it is. But now we're gonna implement it on a heat map, okay? Now let me just clear this out and change the slide here. So what's nice about this is that level four is going to give us a consistency on how long that trader's been out there for. And also you could see the more predominant iceberg orders than other different price levels. So as much as you might see buyers and sellers at one price, you could see it and say, wow, this guy's been out there since nine o'clock this morning and he's been here till four. No wonder why.  So let me show you an example. Like here we're looking at Amazon, right? So you see this big red line right here? That red line makes up over 141,000 shares. Now there are buyers at 5,900, 2,000 and you're coming up to this 14,000 share seller and another 58,000 at 100. So what does that become? A resistance, right? That's gonna resist them going higher, big sellers. But there are times and times where resistance levels get broken and you wanna know why. And the big reason why is because what happens if somebody bought it from that person? You know, that could happen. You see stocks break resistance levels all the time. So when you wanna try to figure out what a breakout is, that is a breakout. So I'm not trying to contradict what I'm saying about support and resistance levels, buyers and sellers. But if you wanna know how stocks break a resistance, you gotta remember that resistance was an order that was probably in the past and is now in the future. And then or maybe the order that was in the past is not in the future anymore. But in this situation he was and that's what drives the stock to go higher. Just like we're looking at Coinbase right here. Here's a stock that took a nice little run from 65 up to 68. And you could see how it came right back down to 66 and all of a sudden, you see this little red line starting to show up. Somebody all decided around, I don't know, 10, 10, I wanna sell 48,000 shares, right? And guess what? You think you're the only one that sees that? Cause a lot of you aren't, but the street does. And guess what ends up happening? 59,000 becomes another 17,000. And then you have a stock that goes from $68,000 down to 64 and you're sitting there wondering what made this stock go up? It was a great news on it. The stock was awesome, everything. Well, I'm gonna ask everybody this question. How much smarter and better trading decisions if you were able to see these big block iceberg orders?  I don't think so. I don't think you're putting $3 million into a stock, but I sure damn well wish I knew who was and you're not seeing it. You see what I'm saying? This is why people fail in trading.  Well, it's time to stop being and pretending to be a trader and it's time to start treating it and doing it right. And what I wanna do is I wanna invite all of you to come into my trading room and to see if this stuff really does work and if it does make sense because the best thing that's gonna happen to you is that you're gonna find out that you should have never did your trades before and maybe this is not for something for you to do and you know what, that's okay.   And actually I'm glad I didn't lock myself into something. So, but then there are some people like, damn, this is not, this is what I want, but now that I know this exists, oh my God, that's changed my whole life. It's a totally different bowl game. That's what I want. That's the kind of experience I want you to have and that's the experience why Cybertrade University has been endorsed by almost every broker term in the industry because we go out there and we work with them and we train their students so they know what they're doing because training someone is a lot of work. I don't know, does anyone here have kids that go to, anyone have children? Anyone has sent their kids to school, to college? Forget school, you have no choice, but anyone go to college? Oh my, I have two boys, right? And I had one of my oldest son was dying to go to the school. Dying, he says, oh, I gotta go there, I gotta go there, I gotta go there. After the first semester, he says, that I can't take same one.  And I said, well, you didn't go look at the other ones. Okay, you wanted to go this one, your heart was sold on this one. You didn't get the other ones a chance. Then when we finally looked around, he was the happiest person ever. He actually didn't want to leave, okay? We couldn't even get him home for the holidays. He was having so much fun. He was learning and everything else. And he ended up being the top of his class, you know? So you see, education is very important to us, but you gotta make sure it's something that you get, but you can't go out there and try to do it on your own. Now on question in general, what is the define of level one and level two? Okay, so that's a great question. Let me bring this up to you and show you what you're seeing.  So what you're looking at right here, this is called level two quotes, okay? So level one is right up on top. This is level one. You're just seeing the best bid and the best offer. These are the buyers and these are the sellers. This is level two, but on level two, you're seeing all different exchanges and what the stock is trading at that exchange. What you're not seeing is who's at that exchange and who else is looking to buy below it? That's the big difference. Does that make sense? You see how like all of a sudden your brokerage firm might be offering, oh yeah, we got real time quotes. Oh yeah, we got level two, garbage. Holy waste of time. It's not telling you anything. And that's why you gotta have the right tools. Well, Raymond, that's a great question and I'm gonna show you how to do that. Okay, we didn't get there yet, but thanks for sharing that, okay? I'm gonna invite you to come and see it live, all right? Now, this is basically the trading room. It's actually, we run all day long, all right? And hold on a second here. Here's our trading room right now. This is the live trading room. We're actually right now, just to show you what we got going on. They're all trading and they're looking at a stock hold S, CLX. And you can see our instructors, our C2 staff. You can see all our traders down here. You'll be a part of this list right here. We're very, very selective who we let in here, okay? Listen, if I wanna have full 5,000 people in here, I could do that. I don't wanna have full 5,000 people. You don't wanna be in there. So this is a very exclusive room and you're gonna see how we're gonna basically, how we're gonna vet who is allowed in there and who's not allowed in there. But everything that you talked about, how to find all that stuff and the traders, we're gonna talk about that. Now, couple of questions. I don't wanna answer some questions, Dan. I'll get to your question in the next moment, okay? Here's a couple of questions people ask. How much money do I need to start? Well, let me tell you how much you need. Zero. All you need before you go out of your way buy these fancy computers, these monitors, brokerage firm account. You don't need any of that stuff right now. What you need right now is you need to see if this is for you or not. If you can understand it, if it's too fast, if it's too slow, I don't know where it is. That's so basically money-wise, you don't need anything. And you also do not need a brokerage firm account. If you have one, that's great, okay? But don't go out of your way. You don't need to start off. That's the worst thing that can happen. That's like saying, let me go buy a car and you didn't even learn how to drive it yet. We don't know how that story is gonna end. So this is what I'm asking. Everybody have their phone? Okay, take your phone right now and I want you to scan that QR code right there right now. And if you don't, I'm gonna post a link right now in the trading room. This is what I'm asking for, $9 to do a trial. $9, let me tell you why. We could have you come in for free. And we did it in the past couple of weeks. It was a disaster, all right? It was a complete disaster. You know what? We're not looking for free people because unfortunately, if somebody's looking for free stuff, that's all they're gonna get. To go into this business to trade, I just told you, you could go to NASDAQ, pay $15. And you know what? I can almost guarantee you that half of you didn't click on that link. Maybe because you're here or you're not ready yet. If you wanna be getting this in the market, listen, when you turn on the TV, what do they talk about every day? The stock market, the stock market, inflation, you know what I mean? The dollar, it affects you every day. So what I'm looking for is serious traders.  I'm gonna give you not one day, but I'm gonna give you one week in my trading room because you know what? Maybe one day is not enough. Maybe you had to leave and go to the doctor or whatever it is. So I'm gonna give you one week. And at the end of that week, if you're not satisfied, I'll give you $9 back. Money back guarantee. I don't need you to screw me. I don't need anything. I'm just looking for traders I could trade with. Now this is what you're gonna get. You're gonna get the trading room. You're gonna get the alert service. You're gonna get weekly, we're gonna do a weekly watch lists. You're gonna get workshops. Okay, we're gonna teach you how to use level three, level four, level one, level two.  Because I wanna make sure that you're making the right decision before you go out there and do this. And also you're gonna get 100 hours of our library. We're gonna throw that in there. This is all for $9. $9, that's all it is. And you know what? At the end of the week, if you're not satisfied, I'll give you your $9 back guaranteed. I'm just looking for real traders. This is not a scam, there's not anything else. There's the 30 years. Okay, I'm just looking for serious traders. Now, as a bonus, you could go to Amazon, you could buy my number one best seller, how to beat market makers at their own game, published by Wiley, one of the most prestigious publishing companies in the industry, cost $45. I'll give it to you for $9. It's part of the deal, $9. I'm throwing that in there, okay? All of that. Now, I'm gonna do one more bonus, okay? Just one more. If you register right now, you have the opportunity to get a free coaching class with me on the phone. That's right, me personally. Now, some people ask, why would Fausto be guru, very well-known in the trading community on TV? Why would he pick up the phone? I could talk to the president of the company. Yes, he'd tell you why.  Look at me as being your doctor.  Because God, if it's something that's happening, it's a waste of your time, it's a waste of my time. Now, I wanna do a couple of shout outs really quick, because I got a bunch of people that are just registered right now, all right? Heidi, I guess you were the one that was always chatting away. You didn't waste any time, did you? You got registered. Welcome aboard, look forward to teaching you. Casley, got your registration, welcome aboard. Thank you very much, appreciate it. Elizabeth, just got your registration, welcome aboard. All right, now, does anyone have any questions whatsoever? Any questions? A couple of them came up here across here. When can I start? So that's a good question. No one can get into the trading room until we do a walkthrough. You can talk to my staff, they're gonna show you what's going on, because when you go in there, you're gonna be totally confused. You're like, okay, what do I do? Where do I look? We want you to have a very good experience. And it's gotta talk to our staff, make an appointment, you can be on the phone with them about five minutes.  And like I said, at the end of the week, it's not your style, we'll give you money back. But I probably recommend, remember the markets closed tomorrow due to Good Friday, but you could probably start on Monday. I mean, listen, let me explain something to you. It's freshening your mind, start right away. Don't wait, I gotta talk to my wife, I gotta talk to my husband. It's nine F-in dollars, that's all it is. And that could change your life. And there's only way to find out. Couple of people also registered right now. I got, who is this? Avelmer, A-R-E, I got your registration. Who else I just got? Someone else just came in here. Marina signed, it's got your registration. Just show you there right here. These are all the people that just registered right here. It's getting a registration. Someone just bought one of the courses, but yeah, everybody's registering. Just click on that link. Do you have a link for the recording presentation? Sam, yes. So at the end of this presentation, we will give you the recording to it. But what do you need the recording for? What do you want to want? Sam, just pay the nine dollars and get in the room for a week and get hundreds of hours of recordings. How about that? Okay, let me make it easy for you. Listen, I love what I do, I have a passion to it, but I hate seeing people lose money.  You know what we want you to do? We want you to go out there and we want you to see other traders that they're making money in the trading room. And most importantly, we want you to see how they control their losses. Your biggest issue is you don't know how to stop taking losses, you know? And everyone out there, they just don't, and they don't know what to trade with. They're trading by themselves. They're in the basement, you know what I mean? Like, read the book. It's a fast read, okay? I did that on purpose. You're gonna see the lifestyle of what it's like to be a trader, what you're supposed to do, what you need to do, how to become very successful. It's not really that much to ask. Couple of the people just registered, Chase just got your registration. Yolanda got your registration, welcome aboard. Debbie got your registration from Chicago, welcome aboard. All right, good. Thank you very much. Jenny has a question. I did not get my one-on-one with you from last week. Can I get another one this week? Yes, Jenny, you know what? Talk to your education advisor, okay? Talk to your education advisor, and like I said, listen, I'm very busy, you know what I mean? So, you know, I don't know what had happened, whatever it is. There's only so many hours I can give up because I trade my traders. So just get a hold of them and they'll figure something out for you, okay? And let you know what my schedule. And if you don't get to be able to talk to me, you can talk to one of the other instructors too. Raymond just got your registration, Mananez, M-O-N-I-Z, sorry about that. Just got your registration, all right? Snapper, I saw you chatting, I didn't see you register yet. Tim, like, listen, this is what I'm trying to tell you. You can go to NASDAQ pay $15, or you can come here, pay $9, see what it's like before you go spend the $15, right? So the thing is, why not go out there and see how Wall Street traders trade, have a seat on the exchange, and start from somewhere? Because that's why we're here, right? Listen, how many of you here trade options? How many trade options, raise your hand. Actually, I'll do a poll, how about that? Because I don't want you guys hurt your fingers, all right, you're typing, there we go, here, I'm gonna launch something really quick. Won't let me launch it. All right, well, I guess that ends that. Something happened over here at that launch. Okay, because I guess I'm on the last slide. You do, okay, so regarding about options, let me ask you something, what makes an option move? It's the movement of the stock. Think how much smarter and better trade decisions if you just knew how to trade the stock, which is black and white, and then you know what options to trade. How many of you here swing trade? How do you think things turn into a swing trade? It happens over the course of the day. You see, so if you knew what happened over the course of the day, then you'd be like, you know what, this stock looks like a good swing trade now, it's starting to trend up, it's doing well. See, it all starts from the beginning, and the beginning is, if you know how to day trade, you'd be that much better at a swing trade, and then a swing trade turns into an option trade, okay? Now, very, very important fellow traders, the ones that are registering, you'll notice you have a questionnaire. We ask five very important questions. Please let us know who trains you, all right? So we wanna make sure that we have an idea of what kind of style you have. Do you have level three or level four quotes? What broker you have? Let me tell you, 80% of the brokers out there will not give you the right access to have a seat on the exchange. Some of them do, you just didn't have it set up properly. So let us know exactly who you have so we can go from there. Couple other, Ernie just got your registration. Just reading them up over here, just see if two of you just registered right now. Ernie's got your registration, Haas, Ron, just got your registration right here. It was a beach champ, okay? Just got your registration, welcome aboard, all right? My fingers are okay, I trade options, Keith is saying. Keith, it's good to see you. Keith's one of actually one of my students. Keith Anderson, that's you, right? I always remember him because my best friend from high school was named Keith Anderson. Miss Jenny just got your registration, welcome aboard. There you go, there you are Jenny, is that you? Finally got your registration, welcome aboard. All right, so there you go, there you got the QR code guys. Listen, level three, level four, follow the money, know the iceberg orders, see what's moving. Look, they got a one stock that's moving great right now. Look at this stock right here. Look what they're trading, pushing up towards $3.   Look how nice this stock is moving. Probably want to see it here probably a little bit better. Look at this thing, it just ran from 270 to almost 290. If you bought a thousand shares of that stock, guess what, you made $200. That's a hell of a good deal of them spending nine bucks, it paid for itself. Yep, S-O-U-N, it's moving up nicely. You can see how traders have been watching it. They're also looking at sobbing. Right now is the slow time of the market in the middle of lunchtime, that's why we do these events right now, but let me tell you, there has been a lot of good action. There was actually one stock, before we go, let me show you one stock that was trading yesterday, which was like ridiculous. Hold on, let me show you one good stock that was unbelievably yesterday. Did you guys see this stock yesterday? SUXI, this stock at 130 ran from $9 to $17 in about two hours. You could have came in late. You could have got our alerts. I'll even show you the alerts. Look, here's our alerts right here. Here's our alerts right here. This is from yesterday. That was this morning. You could see right here, there's the watch list. And you could see here how we kind of bring it up. We talked about the stocks that got halted, what moved, what came up. See right here, you can see the halts. There's another stock that moved, AT&F, all of them. They're right there. All these alerts you're gonna get. All right? All right, listen. I can't convince anyone anymore if you haven't registered yet. So I'm gonna close out. Couple of quick little shout outs. Troy got your registration. Welcome aboard as I just saw just come in. And Albert just got your registration. Congratulations. Look forward to seeing you in the trading room. All right, so anyway, listen. If you haven't registered, I understand. Maybe you're not ready yet. Maybe you gotta think about it, okay? Maybe you're getting ready to go to Easter vacation, whatever it is. But that's okay. We're not going anywhere. But hopefully, maybe down the road if you are. But if you are registered, listen. Very important for everyone that had registered.  You've probably got an email already. Book your appointment immediately. Do not procrastinate, okay? Do the walkthrough, get into that trading room. And then all we want you to do is watch, okay? Don't buy anything. Don't do anything. What your goal is this. You do not wanna judge us on our winners.  And you wanna see how we get out of them and how we control them. Cause that's everyone's biggest problem, all right? So thanks for watching, everybody. Look forward to seeing you in the trading room. Happy Passover and happy Easter for everyone who's celebrating. And we'll see you next week. And don't get markets closed tomorrow. Thanks for listening, everybody. Happy trading and be safe.


Du-du-du-du-du-gu-du-du-du-du-du-du-du-du-dum Du-du-du-du-du-du-du-du-du-du-du-du-du-du-du-du-du-du-du-du-du-du-du-du-du-du Du-du-du-du-du-du-du-du-du-du-du-du-du-du-du-du It was a cold and rainy day in Fantasyland, and there I was, minding my own business by the campfire when Out of the Blue this villager dude comes up to me and asks, Hey, you're a hero, aren't you? Like a liar, I respond it, Yes, of course I am! And this villager tells me of a predicament he's having where he'd like to get from one end of the town to the other. night is dark and full of terror so he wants me to go with him because of all the people sitting at this campfire at the twink with the short sword was the optimal bodyguard. It is the fourteenth day of the fourteenth month of the fourteenth year inside of the city of Athens in the barraming of Kulia within the kingdom of Dupont.


So, by this point, we've actually now covered all the core concepts of querying data, but what about actually adding data into the database or updating data, manipulating data? Well, when it comes to adding a row for a table, this is called an insert operation. And unsurprisingly, if you want to insert a new row, you have to provide a value for each column. So, here in our cats table, we're inserting a new row and we're providing a name value for mittens, a lives value two, and a hair length short. And now we have a cat mittens with two lives and short hair. When it comes time to remove rows from a table to delete them, what we do is we specify a predicate, a predicate used to filter rows to select rows and then delete them. So, here in our planets table, if we delete rows by specifying a predicate of distance from sun greater than 100 million miles, that's effectively specifying Uranus, Neptune, Jupiter, Saturn, and Mars, and then deleting them. If we want to change data in existing rows, this is called an update operation. And first, we specify which rows we want to update with a predicate. And of course, we specify which column or columns we wish to update with a new value and what those new values should be. So here we're updating simply the column lives with a value of five in all rows where the name value is princess. So whatever number of lives these two rows with the name value princess had before, now both of those rows have the value of five in the lives column. In our database schemas, when we sort out what tables we need and what columns they should have, we generally designate for each table a primary key. The primary key of a table is the column or set of columns, the values of which are used to uniquely identify each row. In this example table here, it makes most sense to designate the make and color columns together as being the primary key because presumably you wouldn't have two rows where the make and the color are the same. It wouldn't make sense, for example, to have two rows where the make in both is Toyota and the color in both is blue because there's only one quantity of cars for each combination of make and color. In real world practice, however, it's by far most common to give each table its own ID column which has an arbitrary integer in it, a unique integer, and it's these ID columns which are most commonly used for primary keys. In this example here, you'll notice there's really no relationship between the ID value and the content of that row. It's really just totally arbitrary what the ID value is. The only important thing is that it stays constant for that row. To facilitate this use of integer IDs as primary keys, most databases have a feature whereby you could declare a column, especially as a primary key column, and the database will actually auto-generate an ID number for that row. So you, when you insert a new row into the table, you don't have to specify an ID. In fact, you shouldn't. The database itself will actually automatically create an ID number for that row for you. This makes a lot of sense because it's then the responsibility of the database to ensure that ID is actually unique, that it's not already being used by any other row in that table. What's called a foreign key is simply a reference to a primary key of another table. So here, for example, we have a table on the left of colors and a table on the right of people. And the color table has an ID column designated as that table's primary key. Again, the values in these ID columns, when we add a new color, they're generally just auto-generated by the database itself. For simplicity here, I've simply have chosen values starting from one down to five, just because it keeps the numbers simple. In a real database, when you insert rows, they might start numbered from one. They might start numbered from zero. They might start numbered from any random number, actually. So the IDs that get auto-generated aren't necessarily small numbers starting from one. But in any case, looking over at the table of people, we have the name of each person and then we have their favorite color. And the favorite color column is a foreign key because it's simply a recorded value that references the primary ID of another table, the color table. So according to the data in this table, the person named Alan, their favorite color is orange. And same for Chelsea, their favorite color is also orange. Sam, though, his favorite color is the one with ID 2, green. Now, the thing to note here is that primary keys and foreign keys are really what form the relationships between tables. In fact, the most common use of joins is to take two tables where one has a foreign key pointing to the primary key of the other. And once we take the cross-joint of those two tables, we then filter for the rows where the foreign key value of the one matches the primary key value of the other. And then we'd end up with this table, which is what we'd want when we wanted to query and find out, hey, that favorite color of Alan's, what's the actual name of that color? Because if we just query the person table itself, that only gives us the IDs of the colors. We want the actual name of the color, which is contained in the color table. Now, of course, the objection here is, well, why did we put the names of the colors in a separate table to begin with? Why not just stuff them into the person table such that the person table has a column that simply reads color? That'd be far simpler. Well, in a trivial example like this, doing that would have probably made more sense. But as you'll see when we get into more complicated schemas, more complicated database designs, such thinking tends to lead you astray. In fact, as we'll discuss in a moment, there are formal rules that have been devised for how exactly you should split your data up into multiple tables in your relational database. Before getting into those more formal rules, though, there are first two simple guidelines which are very important to keep in mind. And those two guidelines concern how to best represent relationships which are called one-to-many relationships and what are called many-to-many relationships. First a one-to-many relationship is like the one we just saw. And for any one color, there are many people who might have that as their favorite color. So one color, many people. And the way this gets expressed is that we have the two separate tables, one for the colors, one for the people, and the people table has a foreign key pointing to the primary key of the colors. Or for another example, one person might make multiple orders. So if you have a table of people and you have a table of orders, the orders table has a foreign key referencing the primary key of the person's table. Now the best approach for many-to-many relationships is less obvious because it involves the introduction of a third table. So here, for example, we have authors and we have books. And each author might have multiple books, but each book likewise might have multiple authors. The only way to properly express this is by introducing a third table which matches up authors with books. And this third table you will note actually has two foreign keys. One for author IDs and one for book IDs. And having more than one foreign key is actually perfectly fine. Foreign keys are not like primary keys. A table always has just one primary key, but it can have as many foreign keys as are necessary. Another kind of many-to-many relationship is when you have one kind of entity and you want to have multiple relationships between any pairs of those entities. Here for example, we have a table of people and we want to express the friendship relationships between those people. We can't do that in the person table itself because each person has potentially multiple friends. So again to express this many-to-many relationship, we have to introduce another table just for that purpose. Now I should say it's actually kind of hard to identify the scenario as a many-to-many relationship scenario. It's a bit deceptive because you think, well, one person has multiple friends. That's one person, many friends, right? Well, the people that you are friends with themselves might likewise have multiple friends. So it's actually many-to-many relationship, not a one-to-many relationship. It's pretty confusing in that regard. But any case, looking at our other table of relationships, the other thing that makes this odd is that friendship we usually think of as a two-way relationship, it goes both ways. So when we say that person one has friend with ID two, well then we also say that person two is friends with person one. If I'm friends with you, presumably you're friends with me, presumably. Now it's actually debatable whether you should have to express these relationships twice. You could establish a convention, a rule for your database whereby the friendship is only expressed in one direction, maybe you'd have a rule deciding which way you would express that relationship, that two-way relationship. It's actually a bit of a dilemma. The downside of expressing the relationships both ways is that you have, for one relationship, two rows. And so if you want to update, modify, or remove some existing relationship, you'd have to make sure to do so in pairs. You'd have to make sure to remove two rows at a time, the two corresponding rows. On the other hand, if you chose to express these two-way relationships just by using one row such that say you'd have person one with friend two but you'd omit the row person two friend one, you could choose to do that. It would likely though complicate any query you wanted to do, like you wanted to find out everyone who's friends with this certain person, you'd have to do a lot more work to figure that out if you only expressed the relationships in one direction. The takeaway from this is that the relational model is sometimes kind of an awkward fit for expressing certain things. In time though, with some practice, you'll find that you'll adjust and you'll be able to fit most everything pretty easily into the relational model and you'll find tricks to work around the other cases. The formal rules I mentioned earlier that we used to devise the structure of our database, the schema for our database, these are called the rules of normalization. The primary point of the normalization process is to minimize any redundancies. That is to ensure that when we insert new data into the database, we're only inserting it into one place, not multiple places. Not only do such redundancies lead to a waste of storage space and to increased complexity in your queries. They also tend to lead to consistency problems because if you record same data in multiple locations, that means when you want to update that data, delete that data, you have to ensure to do it in all of those places all at once every time. If you're not careful or if something goes wrong, you end up with data which has been half updated, so you have conflicting values in your database, which is generally not a good thing. The whole notion of normalization was actually originally devised by Edgar Codd himself, the person who invented relational databases, and in fact normalization was sort of an integral concept to the whole thing. Very shortly after he introduced the relational model itself, Codd also introduced the first three of what are called the normal forms. There's the first normal form, the second normal form, third normal form, fourth normal form, fifth normal form, and sixth normal form. Originally, Codd himself only introduced the first three. The fourth and fifth were introduced by other people later in the 70s, and then the rule of the sixth normal form was actually devised and introduced actually quite recently in about 2003, I believe. And the general gist of these normal forms is that they are progressive. So when you normalize your database, if you attain the level of the first normal form, you then from there can proceed to the second normal form, the third normal form, the fourth normal form, and so forth. So if your database conforms to say the third normal form then implicitly it also conforms to the second normal form and the first normal form. Now there's actually kind of a reason why the first three normal forms were introduced very early on and then the fourth and fifth came later and then the sixth way later. And that is that in practice, fourth normal form, fifth normal form, and sixth normal form are just not nearly as critical as normalizing your database up to the third normal form. Third normal form is actually what most people tend to aim for when they normalize their database. Most people don't fret too much about going beyond that. And actually it works out that in the large majority of cases, if you've normalized your database to the third normal form, it works out in most cases that the database most likely also conforms to fourth and fifth normal form without even trying to be clear. It is possible to conform to third normal form but not fourth or fifth normal form. It's just not likely, it doesn't come up in most situations really. So with that all in mind, we're only going to discuss the first three normal forms because they, as I said, are really the ones really relevant to most people. Before we get to those, Codd himself actually summed up the purpose of normalization pretty succinctly. First off, the point is to free the collection of relations from undesirable insertion, update and deletion dependencies. Again, relation is just Codd's term for what we usually call tables. And what he means by dependency here is a scenario where when you modify or insert or delete something from one table, you need to, for the sake of consistency, perform some other action on another table. Those are dependencies between tables. And while it's true that in some scenarios, such relationships really are unavoidable, they're really necessary, one point of normalization is to try and minimize those dependencies, because, well, the fewer the better. Codd also says that the point of normalization is to reduce the need for restructuring the collection of relations as new types of data are introduced and thus increase the lifespan of application programs. What he's saying here is that ideally when we add new tables to a database, it shouldn't require having to update existing tables or modify their structure. That'd be quite bad and intrusive, right? It's really important to have the flexibility to add new tables as easily as possible. In bullet point three here, he says that the point of normalization is to make the relational model more informative to users. And what I think he means thereby informative is that if somewhere to look at the schema of your database, look at the design of the tables, it should be quite evident looking at any one table what its purpose is. What you tend to get in an improperly designed database schema is a bunch of tables that have sort of nebulous roles. You're not really clear on what purpose those tables serve or how they relate to the other tables. Lastly, Codd says that normalization is also for the purpose of making the collection of relations neutral to the query statistics, where these statistics are liable to change as time goes by. That's a bit tricky to parse, but what he means first by the relations being neutral to the query statistics, he means that the database shouldn't make it unduly hard to write certain queries because of how the database is structured. And not only should those queries be harder for a human author to write, they shouldn't be especially more onerous for the database itself to execute. But of course, some queries you write are going to be naturally more complex than others, just because maybe they involve many more tables. And they're also potentially going to be more resource incentive. They're going to take longer for the database to process simply because they involve more data and more work for the database to do. However, Codd is basically saying here that normalization will prevent scenarios where cases which should be simple and which should run fast aren't going to be artificially hard to write or artificially overly taxing on the database. That's basically what he's saying. So now let's actually look at the first of these normal forms. The first normal form is the easiest to state, certainly. It's usually just expressed as no repeating groups. Tables should not have repeating groups. The only difficult part about this first normal form is an understanding, well, what the hell is a repeating group? And there's a little bit of a disagreement among competing interpretations of this first normal form. But at least what people agree on is that it means that there should be no ordering among the rows or columns in your table. And in practice what that means is that when you insert data into your database row by row, you the user of the database understand that the database is not maintaining that order. And so when you do a query later on, you're not going to get back the data in the same order. That's in practice really what that means. No repeating groups means that you also shouldn't have duplicate rows. And in practice really what that means is every table should have a primary key. As long as you have a primary key for every table, you're not going to have duplicate rows. No repeating groups is also interpreted as meaning that for any column, that column only really expresses one attribute. You shouldn't try and surreptitiously stuff multiple attributes into one. You don't want multiple values per column. And similarly, for every value in a cell, that is every intersection of every row and every column, each cell of data, it should never have more than one value in any cell, which is kind of like saying the same thing that every column should just express one attribute. So the first normal form is really not hard to understand, even if there are maybe some competing interpretations for more subtle cases. But in general, what I interpreted as meaning is just make sure your tables are really tables. No ordering of the rows, no ordering of the columns, one value per cell. And that's pretty much all it is. The second normal form is maybe a bit trickier. It's certainly more of a mouthful to say. No non-prime attribute is dependent on any proper subset of any candidate key. And to unpack that, we first have to define some of those terms. First off, what's called a super key is just any combination of attributes of columns. It's any set of columns that could be used to uniquely identify each row. So in this example table here, there are a couple super keys. The in combination of skill and employee, that's a super key. The skill and current work location would be a super key. Or the combination of all three together would be another super key. What are called candidate keys, however, are a subset of the super keys. The candidate keys are the super keys which don't have any so-called extraneous information in them. It's a minimal super key is one way to think of it. Another way to put it is that a candidate key would be a valid selection as the primary key for the table. And in this example here, there's really only one candidate key. And that is the combination of employee and skill. So once again, candidate key simply means a set of keys which could validly be selected as the primary key for that table.  So again, our candidate key here is employee and skill together. The two proper subsets of that are the employee column by itself and the skill column by itself. The combination of employee and skill together, that is a subset of itself, of employee and skill, but it's not a proper subset. So that's all what proper subset means. And finally, the prime attribute is a column which is part of a candidate key. So a non-prime attribute here is current work location because it doesn't belong to any candidate key. So to ask if this table is conformant to the second normal form, we ask is the current work location column dependent upon either the skill column or the employee column. And the answer is that the current work location is dependent upon employee because presumably it's something that corresponds to the employee. One employee has one current work location, right? So this is no good. We have a non-prime attribute which is dependent upon a proper subset of a candidate key. The most sensible way of correcting this example is to split it into two tables, one for employees and a second table just expressing the relationship between employees and their skills. This is actually an example of a many-to-many relationship. For each employee, there are potentially multiple skills which that employee has and for each skill, there are potentially multiple employees which have that skill. So if you just went by that guideline, you would very quickly see there's a problem with the original table because one single table cannot express a many-to-many relationship. You have to bring in another table for that purpose. And actually, if we recognize that this is a many-to-many relationship, we should see here that there's still really a problem and that is that the skills themselves should have their own separate table. And then this table expressing the relationships between the two would be between the primary keys for the employee and the primary keys for the skills. Well, the arrangement here might seem OK. It's going to become problematic as soon as we decide that skills themselves are something we want to provide more information about. As soon as we decide that a skill is something which is its own entity worthy of having its own attributes, that's when we'll want skills themselves to be in their own table. In a table in third normal form, every non-prime attribute is directly dependent upon every super key. And remember, super key means any set of columns which together uniquely identifies a row. And non-prime attributes are those attributes, those columns which aren't part of any candidate key in the table. So the question is, what does dependent mean here? And actually, there's a more popular, easier to remember formulation for the third normal form that makes this pretty clear. And the way this goes is every non-prime attribute provides a fact about the key, the whole key, and nothing but the key. And looking at an example here which violates this rule, we have this table of tournaments and their winners, which right off the bat, just saying that tournaments and winners should raise alarm bells because tables should be about one sort of thing, not multiple things. But anyway, here the primary key of the table is the combination of tournament and year, assuming of course that one individual tournament is only held once a year. And so what we need to ask about the columns winner and winner date of birth here, the non-prime attributes is, are they providing a fact about the key, the whole key, and nothing but the key? And in the case of the winner column, that one does check out, but winner date of birth, again, right there in the name of the column that's telling you that something's up here because it's winner date of birth, not just date of birth, it's the date of birth of the winner, not of the tournament. So it's not a fact about the key and nothing but the key, it's really a fact about the winner. So the dependency here between winner date of birth and tournament and year, it's not a direct dependency here, it's a transit of dependency where winner date of birth is really dependent upon winner, and winner is what's dependent upon tournament and year. So the solution here, as basically always, is to take this table and just split it into more than one. And so more sensibly, we'd have a table for tournaments and a table for winners. And the winner table has a ID primary key, and the tournament table simply has a foreign key referencing the primary key of the winner table. So that's an example of third normal form. And again, understand that if you're in third normal form, then by definition, you're also in second and first normal forms. And if you want to sum up all these rules into just one common sense slogan, that is to always ask yourself about any table, does this column really belong to this table? And if you just think in those terms, you'll usually catch most of your problems. Just going by that guideline will usually get you most of the way there to third normal form. Finally, one last thing to understand about normalization is that more normalized isn't always better. It turns out there are actually cases where one would actually want to deliberately denormalize their database, that is to take their schema, which is properly normalized, and to actually make it less normalized, effectively to add more redundancy into your tables and your schema. The reason you might do this is for the sake of performance. Having redundant data sometimes can allow for more efficient queries, depending upon what exactly your use cases are. So in practice, we really have this trade-off. If you want to have a very clean database with everything properly organized, then you maximize normalization. If you realize that, wait a minute, there are these few particular cases where we really need to have this data also in this column because trying to join it together with all these other tables and get our data that way, that's just too efficient for something that we're doing maybe many times a minute or something. And so in those cases, you actually deliberately denormalize your database and add in some redundant data. So denormalization is a tool, basically, of optimization. And database optimization is a whole subject unto itself that we're just not going to get into here.