We have been talking about geomaterial characterization in general and in particular the chemical characterization and I will continue with this. In today's discussion I will give you a brief idea about the contaminant transport in porous media and this is important to be studied at this juncture before we start dwelling into desorption and desorption studies because the pretext of sorption and desorption is contaminant transport in porous media. When the interaction of contaminants occurs with the porous media then only we talk about this sorption and desorption process. Now this is a multidisciplinary subject, many technologists would utilize the concept of sorption and desorption and very evolving area particularly in the realm of environmental geomechanics and hope you will realize that this becomes very, very important due to the fact that is the quantification of the interaction which we have been studying since long. So if you want to study how to quantify the interaction between contaminants and the porous media the best way would be to study the sorption, desorption mechanisms and from there you quantify the whole process. And of course we will continue with our discussions on thermal, electrical and magnetic characterization subsequently. So to begin with the contaminant transport in porous media hope all of you understand we have cited several situations, examples where the contaminants come in contact with the porous media or the soil mass or the geomaterials and this also has the pretext to the fact that flow through porous media is very well understood when we deal with water that is you know you have already talked about the seepage consolidation and stability of the structures where we have discussed the influence of water seeping through the porous system. Now if this water contains contaminants and these contaminants are migrating through the porous media then the entire mechanics or the interaction process becomes difficult and intricate to understand and that is what actually we are trying to attempt to study. So the concept of hydraulic conductivity is quite well established you have done constant head test and falling head test the simple analogy which comes to my mind is if I adulterate the water with some contaminants and if I allow this water to migrate through the porous media and if I ask you how much the hydraulic conductivity has changed this is one question. The question would be what is the concentration gradient of the contaminants which have been retained by the soil mass you know when the contamination is passing through this third could be what is the fate of the contaminants in the soil mass. So these are the three issues which we are bothered about and we would like to study. So when chemicals flow through the porous media this becomes very interesting important and contemporary situation very practical situation because under no circumstances the water which is flowing in the porous media in real life is going to be you know demineralized water or saline water or it could be contaminated water. So we have cited several examples where the liquid form of contaminants starts migrating through the porous media waste storage facilities landfills mostly and when the soils become contaminated and how would you remediate them and particularly when the leaching is occurring in the liquid phase. Contaminants have to be defined here before we enter into this discussion of contaminant transport through porous media. So we have to understand what is the basic characteristics of contaminants these are the inorganic species or these could be organic species also this could be reactive or non-reactive also you know this could be radioactive and non-reactive also. So sometimes we call the non-reactive contaminants as conservative contaminants alright and conservative contaminants are normally used by us every day we consume lot of salt through our food or through different types of you know eatables and medical scientists would be using different type of salts for tracers suppose if you want to find out what is the problem with your digestive system so they do biopsy they do endoscopy and all those things. So that is also a good example you know you drink some tracers barium chloride mostly those of you who might be aware of this and then they trace how much of the barium chloride has been sobbed by the intestine and that are the places where there is some damage done to the intestine so you can do endoscopy and you can find out you know what is the extent of damage to the colon or intestine. So in this context we use some units to define what is the amount of contaminants which is present in the solvent and the best way to define the concentration of contaminants in the solution would be milligrams of contaminants in 1 liter of water so we call this as milligrams per liters. Another unit could be parts per million so parts per million is 1 gram of the solution which is dissolved in million grams of the another solution I am sorry this should be the grams of the solute divided by millions of grams of the solution. So please correct this is not correct it should be the grams of the solute which is dissolved in the solvent millions of grams of solvent. Now coming to the types of flow through the porous media the basic equation which you have used in the form of the Darcy's law if you remember velocity is proportional to hydraulic gradient. Now this equation can be extended to study how the contaminants are going to migrate through the porous media provided the fabric and the state of stress of the soil sample is not changing or the porous media is not changing. So in this circumstances we can assume that j is equal to phi into x where j is the flow rate alright and phi is a constant we call this as conductivity coefficient or for flow and x is the driving force. So if you use this equation what it shows is that there is a flow of the flux which is occurring and this is equivalent to or equal to the coefficient of the flow multiplied by the driving force. So one of the ways to correlate this equation with the Darcy's law would be q equal to k into i into a. So a is the area of cross section and capital Q upon area of cross section will be small q discharged per unit area and that will be equal to k into i. So there k is nothing but phi gets replaced by k and hydraulic conductivity which is known as hydraulic conductivity and x is nothing but i the driving force. So this part you have already mastered is it not Darcy's law take a sample and apply heads h1 and h2 across the two ends and the delta h which is h1 minus h2 acting over the length of l of the sample is nothing but the hydraulic gradient and small q is k into i. Now I can extend this concept to the flow of current also through the samples is it not. So in that case what I have to do is the sample length remains l and if I know what is the amount of current which is passing through the sample what I have to do is I have to apply v1 and v2 voltage across the sample and then v1 minus v2 gives delta v and the phi term becomes the conductivity term and j is nothing but the flow rate. So flow rate is i current this is equal to conductivity multiplied by delta v upon l. So delta v upon l is also defined as electric field if you remember is it not delta v upon l is the electric field. Now here in case of electricity we use Ohm's law and this Ohm's law is nothing but i equal to specific conductivity multiplied by voltage drop. This can also be extended to heat flow through the geomaterial provided the length of the sample is l and I am applying temperatures t1 and t2 across the two ends. If t1 is greater than t2 the way it was same as v1 greater than v2 and h1 greater than h2. So delta t gives me the temperature gradient and l is the length. So temperature gradient upon l is the temperature gradient multiplied by k. Now this k is the thermal conductivity and q is the heat which is passing through the sample and this is what we define as 4 years law. Now what is remaining is the chemicals alright. So if I apply the concentration of chemicals c1 and c2 across the two ends of the sample this type of situation may occur in the coastal area where you have aquifer of certain length and one side the aquifer is exposed to the seawater saline water and on the other side it is connected to the land towards the land. So c1 is greater than c2 and hence there is a flow of concentration in this direction. So d becomes here the diffusion coefficient multiplied by concentration gradient delta c upon l fixed law. Now I hope you can understand that what we have done is we have you know discretized all the fluxes in their components and then we are saying that if any type of flow has to occur through the porous media it can be modeled by using Darcy's law case of advection flow of water if the water is having species of chemicals then we can use the fixed law and if this water which is having the species of chemicals is at elevated temperature and if it is migrating through the porous media I can utilize Fourier's law to solve this and there could be a situation where the voltage is also acting across the sample electrical voltage or the sample is exposed to the electromagnetic field. So this is where I can use the Ohm's law. So the point is any type of flow which is occurring through the porous media can be discretized into different flux conditions and then I can superimpose them depending upon the nature of the problem and I can solve it alright. So this is the general philosophy of the concept when we talk about how the flow or contaminant transport takes place through porous media. One thing which I would like to highlight is I hope you understand when you apply this law or this equation what is the principle unknown? The principle unknown would be the phi term. So small k hydraulic coefficient or hydraulic conductivity or coefficient of permeability you have obtained by doing different tests in the laboratory or in the field. So you did falling head test, you did constant head test, you did you know triaxial test, you did consolidation test also to get small k value and in field if you have to obtain the hydraulic conductivity then you can do Packer's test or pumping in, pumping out test and so on. So that means the big question is how would you obtain the coefficient of flux transport. So this was quite easy in case of conductivity, electrical conductivity I have to pass current of some value measure the voltage across the two ends and obtain the sigma value alright. In case of heat we will have to pass heat through the soil sample and making sure that heat does not alter the state of the material including the moisture content because I hope you understand that if you are passing the DC current through the sample DC is a heating current. So when you pass DC current through the soil sample the chances are the moisture content may get altered and I am not interested in that. So I will be using AC current most of the time so that AC is a non heating current alright and then I can get the value of thermal conductivity of the soil. Similarly, I will have to do some test to obtain the diffusion coefficient of the contaminants through a porous media. So I am sure you must be realizing that this is a complicated issue. First of all you should be having proper devices which you can utilize to obtain these parameters is this correct? So unfortunately or fortunately when we started working on all these problems there was nothing which was existing in the market. You could not order anything to get off the shelf and say that I will start doing my experiments. So what we have done mostly is we have devised different equipments, we have devised different types of methodologies to obtain all these coefficients and this is where our major emphasis has been. Once you have obtained these coefficients then the life is simple you can plug them in mathematical models and you can do the analysis the way you have done the seepage analysis by using flow nets this is part clear. So the basic challenge is how to get electrical conductivity, how to get thermal conductivity, how to get diffusion coefficients. So from this point onwards my emphasis would be to explain to you how these coefficients were obtained. Of course this is a very elaborate manner in which we have done this and most of these studies have been done by my PhD scholars and each thesis has been attributed to finding out these parameters and the setups which have been done. Sir when chemical flow is taking place like if there is some sorption along with Darcy flow the soil fabric will change. Yes let us start the things with very simple situations alright and then we will complicate it as much as you want do not worry. First to begin with start with the simple things so that life becomes easy this is correct this rule of life. I will answer your questions how everything has been done. Now I am sure you must have realized that what is coupling now if I couple these modules with each other this becomes a coupled flow this is okay. That is a simple mathematical you know superimposition. So let us start understanding the flow through the porous media. So the first thing which comes to mind is you are talking about the advection and all the flow of water because of the hydraulic gradients is advective flow clear. Now we also define this as convection process the you know the idealization would be something like this. If I consider a certain volume of a chemical we call this as a plug. So this is a solute which is getting transported from left to right and this is a situation at t equal to 0 time. Now when t1 is approached this plug simply gets displaced by certain distance and at t2 it gets further displaced by some distance without losing its integrity that is more important. So solute which is also contaminant gets transported through the seepage velocity along with the flowing fluid which is water in response to gradient hydraulic gradient. So we define this as seepage velocity equal to hydraulic gradient multiplied by hydraulic conductivity and divided by the porosity of the porous media. Now this is where I can answer your question that what we are assuming here is that the solute and the porous media both are conservative. So it is a simple situation where you are talking about flow through let us say perfect glass tube alright and contaminants or the solute is let us say conservative salt which is not going to react with the walls of the tube or the soil particles. So under these circumstances what is happening is the entire concentration simply moves from one point to another point without reacting with the porous media and without getting decayed or changed altered. Now if these conditions are valid this contaminant transport is known as advective contaminant transport alright and then I can find out what is the relationship between the time and the seepage velocity. So if I want to find out the time which is required for this plug of contaminant to travel from one point to another point I can use this relationship V s is known L is the distance travelled by the contaminant and I can get the relationship as porosity into L upon k into i. I am sure you must have utilized this equation in your undergraduate when we were talking about let us say in an open channel flow if I ask you to find out the velocity of the water how do it. So you will add some conservative contaminant at a given point and you will measure the concentration at another point you know the time you know the distance you can find out you know what is the velocity of the flowing water. Now again coming back to the point suppose if I want to find out what is the advective mass flux which is passing through the porous media. So advective mass flux is velocity multiplied by concentration and you must have done this analysis V1 into C1 equal to V2 into C2 conserving the mass flux in an open channel flow. So C happens to be the concentration of the solute which is the mass of the solute per unit volume of the mixture and we know other parameters hydraulic conductivity we know the hydraulic gradient this is nothing but the discharge velocity and then I can equate this alright. So this is a simple situation where I can find out what is the mass flux which is entering the soil mass and which is coming out of the soil mass and remember we are assuming that the both contaminants and the porous media are conservative they do not react with each other. The second mechanism of contaminant transport is diffusion what is happening here. Suppose if I take soil sample in a glass tube and if I connect it upstream as well as downstream side with the water path and if I eliminate the delta H how would you eliminate the delta H by keeping H1 and H2 constant but what I will do is I will use the water which is going to pass through the sample by adding some salt into it. So what I have done is by maintaining the heads I have eliminated the advection process is this okay. But now what you will observe is because of the concentration gradient between this and this this side is fresh water this side is contaminated water. Now if you do this experiment what you will observe is I have to take out the sample of the discharge water or even if it is not discharging let us say in the steady state condition I can take some sample from here and I can do ICPMS or atomic absorption spectroscopy to find out what is the concentration of the water on the downstream side. And then if I plot the CT value CT is the concentration of the contaminants present in the downstream side and this is normally normalized with the C0 value initial concentration. So this becomes a non-dimensional term CT upon C0. Now this is plotted on Y axis and time is plotted on T axis any idea what this graph is known as have you ever used this anywhere suppose if I change C by population of a nation. Yes so environmental scientist or the anthropologist will be very eager to find out you know what will be the population after a certain time in our case C is concentration. So this is the concentration which is coming out of the sample at a given time and C0 is the initial concentration. So this becomes a breakthrough curve BTC have you heard about it breakthrough curve in environmental engineering course I am sure you must have talked about the BTCs. It so happens that BTC cannot be equal to 1 why if soil mass and contaminants both are reactive. So this is what answers your question now the moment you take a reactive soil mass and reactive contaminants some sorption is going to occur and because of that CT is always going to be less than C0 value. In a totally conservative system we do not talk about the concentrations but there could be another situation that you have a reactive contaminant which is passing through a conservative soil mass. So there will not be any sorption so CT by C0 could be equal to 1. Now this graph the moment you get will give you the diffusion coefficient capital D alright. So this is a simple way now what I have to do is I have to create instrument in such a manner where I will expose the sample on one side to higher concentration another side to the lower concentration wait for some time let the steady state diffusion process set up into it draw this relationship get the slope and that is the diffusion coefficient alright. So by definition the way we define this is solute or contaminants this is migrating through the sample in the absence of any hydraulic head. In real life we would have a situation where advection also gets coupled with diffusive contaminant transport alright because you cannot stop it. So this becomes advective diffusive contaminant transport where the heads are also acting water is flowing to the porous media and there is a difference in concentration of the chemicals which are being carried by the water when it enters the sample and when it comes out of sample. So this becomes a typical advective diffusive contaminant transport. Again the flow will take place from higher concentration to the lower concentration and delta C is caused by C1-C2 and when this process is going to end when Ct tends to be equal to C0. So the moment the concentration gets equilibrated on both the sides the diffusive contaminant transport is going to cease. At what point we will be taking the slope for diffusion coefficient? Normally we take the linear portion and what I can do is I can manipulate the whole thing in such a manner that I can plot T because these diffusive times are extremely long times. So normally T can be plotted on a log scale. So this becomes a semi log scale I will take the central portion of the curve which is this almost a straight line and that slope is used alright.


We are tributing human qualities to Allah. We act as if Allah has something against us. We act as though Allah is just waiting for us to make a mistake. And we assume that we have to deserve the mercy of Allah by living a nearly perfect life. So what does this thought process tell us? It tells us that from the beginning of this endeavor, or at some point, that we did not place our hope in Allah. Rather, we placed our hope in our good deeds and our abilities. And once we slip, we feel that we don't have the strength to continue. We do not think well enough of Allah to believe that He will guide us through our missteps. And this is what one of the great scholars said, that the sign of the individual relying upon their actions is a loss of hope.


There's my assist back at me up. He's gonna jump it. I'm gonna drag a rush. See the code. He quit How's it going everybody dato do it here back with some more Dragon Ball fighters ranked matches this time playing a pretty standard team of Bardock Super Saiyan Goku and Yamcha It's good to return back to basics every now and again and especially good if you're going up against another don't down having me Oh, oh a little bit of lag. That's fine. I still got the beam assist out. Oh Reflect oh, I shouldn't dash forward. That was my bad. He gets a vanish confirm here What else is he gonna go for though down heavy? He's got the beam assist available to him. He wants that route sliding here comes sliding We're gonna try to stay down. We don't want to get Broly Smash now. Yes Sorry Broly, but I've seen all the tricks and tips for myself. I know when a man gets desperate and wants to grab No Beam assist didn't cover me you you saw me confidently dash up because I was very tech that oh my goodness. I Thought he was gonna drag a rush again. Oh, thankfully we only get to him Nice the ex will thank fish such a good tool. Unfortunately. I didn't block again Vanishing if it hits him does not so we're just gonna go ahead quick tag in here. What's the mix? That's the mix the mix is whipping it People are gonna think I meant to do that. Let's go. All right back him up All right, that's fine. We we'd have vanished there. I'm gonna try to get one myself Unfortunately counter hit damn Sliding on the ground. Oh, what have expected a tag that was aggressive. I Don't even know where the tag came from to be honest Full screen tagging like that. Now that's a tag I can get behind and you want to be careful You don't want to get hit with this ankle beat You don't want to get hit by this either though, okay doesn't go for spear bomb I appreciate it. Then again. He could just use the beam assist Come on, dude. I just said you all he was not I'm not I'm not guard-canceling you best believe I'm not guard canceling. I guard canceled. I lied Wasn't even an audible mix up. I just straight lied to y'all But it was so good sometimes lying is just the way to go get him in the corner. Oh, come on I missed it all But the boy Yaja always there to help Thankfully that hit What the what am I doing? He completely gave up as well. All right beam assist. We're gonna play the Key Blast game here You can't switch out He knew it. He had a spark 6m I was too slow. No bar doc.   I don't regret it. I think I keep him sliding, right? There's no need to bring in GT Goku with that low health. You got to remember. That's an option. Oh, then again I think I did hit him. So maybe I could have just come but Hey, I didn't know that It didn't go with the proper route gonna have to make a little No, none of that. I have nothing I can do here. Unfortunately. I just have to take sliding And I know he's getting a bit frustrated. So I'm gonna I didn't expect that I thought he was gonna do something with some Invincibility maybe a level three Broly's level one all of those options have invincibility. That's what I was more worried about We still have spark cover my option. I gotta expect the Super Dash, right? No Super Dash Okay, he was playing it patient. Unfortunately. I don't know if that was the right move Playing it a little too patient me. That's a lot of dragon balls on the court. Wait a minute Wait, I can drag a rush him in this lag Was that cheap I don't know I feel like that wasn't cheap because it was mostly a joke, right? It was lagging so bad that I had no way of knowing that would hit. I'm upset I'm upset mostly because I didn't do the Wolf Bank fist like I wanted to I thought it was stupid But then it looked like yeah, that was that the actual go-to completely with spear bump. That's the game Game one goes to the boy who Unfortunately kind of sucked. I was not doing great We got a few lucky hits on offense that really pulled through for us in the end But that game was looking like a real mess there That first smash helped out so much. Do we bar dock player? It was too obvious. I had a bar dock out. I bar docked in and then I bar docked out. Oh, man How aggressive are we trying to get here? Coming through a couple overheads. He's trying to mix it up. Just a piece Mmm defense. I like I like defense.  We've never gotten along Over told you that lie was Overhead I tried I tried getting a little reflecting to just the perfect amount of stagger I wanted to test if he was going too slow. Oh This guy's playing real patient. He wants to catch me playing deep Huh What? Man, man sparked right away. Okay. Okay. We're dealing with the different beast He wants to play that momentum base game He knew he had it locked in and he wants to keep it the armor is coming off. Oh, man This is just for the boost and damage The man says the rest of this game is gonna be optimal. I am not losing out on any hypothetical damage But I see you Broly. I can see that I can respect it as well. You know what one thing I can't respect Missus That's why I'm gonna I Was gonna say switch out to get my own but All right, we got to hit this man. We got to hit this man before this gets real tragic looking We hit him operation sick operation number one was success success success.  All right. I've had it up to here What that was not supposed to happen. Oh No, tell me that didn't just happen. I should have level three. I knew it. I was just oh is that a confirm? Yes, yes, it is All right level one should kill here Beautiful, we still have we still have all the tools we need to come back two characters five bars That's a he's getting a little antsy himself though. Oh Super-dash not something I expected from this guy He was waiting for me with the lights. No. Oh, call me mashing by mashing We out. God the frame is bad in this school, dude. All right. We're still kicking. I want that be missus so bad. Oh No, he saw me coming. He saw it coming. Well, he's been doing that all game I really shouldn't have guard canceled. Maybe back dash to buy some time for Bardock, but Overall, I can't I can't I can't say that he saw me coming too much Just just I made it super what? All right, my secret plan was I was thinking about going for Shenron. I don't think that's an option anymore I don't think it was ever an option, but I was feeling it after level three Every hit for the rest of this game has to be amazing Defense for the rest of this set has to be or not set but this game has to be immaculate Immaculate. All right. Here we go Here we go. We're tied one bar of peace even the meters looking pretty similar.   I should have believed in the defense We're reflected that EX. Oh, there's so many options there on defense But we all knew it wasn't gonna be immaculate.  You already know what we serve here Super dash assist with it. Ah, oh Yeah, give give me that.  I saw the frame spiked up Beautiful beautiful. Can we wrap this up with a nice bow though? Come on. Oh, what's the mix?  Let's go all the masters. I hate that second light I wonder if they're gonna touch that up any bit. I don't think they will because it let's be honest It's not really the biggest deal with him. I he's like completely changed strategies again He is not staggering no more me. I don't well. He was only staggering little with GT go-go But the staggering jump bring in yamcha. Oh Imagine if he brought in yamcha, dude.  Let's go. Don't let me catch you. Let me catch you not staggering in proper increments That was lame. That was not as hypocentences. I thought it was gonna be when I was saying it to be honest Are you kidding me? No way to get out though. I really got to stop using these actually Let's be honest. This is smart. Oh, I knew I had that get him sliding Looks like we got the baits back on the menu boys. Get your fishing lines ready. All right. I think we play it nice and slow here Let's go Don't don't even think that was just the lag. It was a little bit the lag But come on. I also I also saw it coming. Oh Wow, we'll visit for 19 frames. Oh Dev take it and look fighters such a beautiful game. Oh This is probably the work. This is probably the worst lag. I've ever seen okay Yeah, it's this is this is genuinely the worst This is that this is bad. This is bad. I have to wait I was molded by the lag come to peace Don't do what you were born to do. He was also molded by the lag. This is The Take your opportunity and seize it. Dato turn fire.  I hate this so much. I hate this Ah, at least you do. I mean, I know it was a joke, but you do get to appreciate how much work goes into fighters here Not with the neck. Oh Appreciate your opportunities Overhead. Oh, I didn't come out. I can see everything I'm too fast for him There's my assist backing me up.  He quit I hope it's just because I'm tired or that is the funniest thing I've ever seen in my life Thank you guys so much for watching if you did find something to enjoy here Please let me know your favorite moment down below and hey hit the like button and subscribe to the channel if you enjoy videos like this You can also check out more videos where I'm more awake on your screen right now Just give any four of those videos a click with that all said I have been Dr. Do it thank you all again for making it to the end of this video and I will see you in the next one


Felly, os fawr am ychydig gydag y breakdown y hon, sydd yn fawr y llai gyrd-giwch, hefyd wedi cael y dyfodol yw gallwn gyfan o'r amser a'r tyfan, ac nawr, fawr hefyd yn hyn oes yn jwydden nhw. Mae gennym yn ychydig fel gweithio.  Yn dweud i ddweud, ac mae'n ddweud i ddweud i eistedd yn ei ddweud i ddweud i ddweud i ddweud i ddweud i ddweud i ddweud. cyn hadd followers ar gyfer y gwaith, ond there is no way, it just seems like a joke. But the left in the UK saw that challenge, and we did something that we actually rarely do in history, which is rather than prematurely admitting defeat, wallowing in, downence, ond, nid yw'n meddwl i'ch gwaith ar y Gweinidol'r models ydy'i llid gan Badi Lindzi, ac nid yw'n meddwl i'r achosi sydd yn ychydigol yn blion y defnyddio. Wrth gŵl hwnneb y gallwn i'ch creu'r wneud o'r ffordd a oedd oherwydd y bwysig o'r ysb cloth a oeddaeth o'r bwysig o'r ffordd o'r ffordd ac oeddaeth o'r ffordd o hollbarthiau. Rwy'n ni'n esudio'r bwysig weithio i un bod hefyd ni'n gweithio'r freid o'r just about defending things like the NHS and all of these things that the Tories are trying to take away from us. But it was actually about proposing something new, and it was about believing in something hopeful. I think we got out of this, temporarily we got out of this mindset that the left of the UK does always have, just this timidness and insecurity about our ideas and our potential power. Rydym, felly, if we gave anything from Corbyn, we would have the idea that we have so much more latent power than we think we do. I have come up with five vague things about things that are achievable and things we should be focusing on in the next five years. Yn cael ei fod yn fwy o'r rym, ac mae'r ffordd y gallu rhoi'r cyffredinol yn ychydig ac yn ymlaen i mwynnu'r rwylau. Ond rwy'n gwybod i'n ffordd y pethau ar y cyfnod i gael eu troi'r ystafell, o'r ideaau y byddwn ni'n dweud yn ff otraf lle i ddweud yn y bwyll, ac yn dweud yn cael ei ddweud. Yn cael ei ddweud. Felly, y first thing, a Ash touched on this before, we can absolutely end detention in the next five years. Absolutely. The movement to end detention has done an incredible job over the past few years and as far as I'm concerned that should be day one of the CorbeIt Government. It's closed down all detention centres. Dydy i'n ddiwrnod am yn y bŵr, ac rhai i'n mynd i'n meddwl y dyma. Felly, rhai am y cy bağn rhaid i ddefnyddio'r cyblion yn y bosib. A gallwn i'n mynd i ddefnyddio'r cyblion, a daint i ddweud yma, rhai'n meddwl ar gyfer bod'n tebyg mwyn i'r llomain. Felly, y gallwn i ddefnyddio y pŵrlau'r llomain ac yn y byddai'n bwch chi fod i'r llomain'n mynd. Ond angen i'n ei hoff yng Ngwch Cymru yn ddelch ar gyfer eu cyd- dewyn respondial fel Cymru, ar y gyfnod ragwydau, ar y dyfosidol, ac oes bwysig o'r mynd yn cyfrifiad roedd hwn. Cymru, oes bwysig, oes bwysig o'r mynd i'r cyfrifiad roedd hwn. ynglyn â bwysig o'r Ministerial Ffasgau Oedd, roedd y mynd iawn gyrdau a'u cyfwaith o'r mynd o'r pwysig o'r mynd i'r cyfrifiad o'r mynd. Mae gweithio, mae yna chi'n gweld ei fod yn y ddechrau i chi'n ei wneud. Mae gennym y byddech chi'n gweithio i'r gwahod gyda'r cyfnod. Mae gyda chi'n gweithio yn y rydyn ni. Rydyn ni'n gofio'n gofio'n nobl. Mae'r lle'r ddiddorol yn olygu. Mae'n ddiddorol sydd yn gallu gweithio'n ei gweithio'n gwneud. Mae'n gweithio i gweithio'n wneud. Mae'r lleidio'n gweithio, mae'n wneud, mae'n gwneudio'n gweithio'n gweithio'n gwneud. o'r rhwng chi'n bwysig sy'n gweithio i'r cyd-gylwyddnig cychwyn nhw. Rwy'n sefydlu cychwyn nhw fynd i'r maen nhw'n agnomrewtol gynhyrchu ac yw'r ffordd yn ysguedd gyda phrygau pobysig, er rwy'n rhaid ei fod ymlaen i'r rhai gael eu lleol yn gyflaen nesaf â hyn a symud. 3. Llywodraeth i'r Localwyd. Felly mae'r ddymil'n lleol yr ysgol yn wneud ar hynny i gynyddiol. I always thought about how I never understood why we always stay in universities. Firstly, loads of people don't go to uni, university-educated people is not a very big segment of the population. Secondly, school kids are super radical, they're super energetic, and they're super open to ideas. They've got a bunch of energy and that's why a lot of the time they feel very weird about the world they're going into and they kind of know something isn't quite right and that combined with energy is why they're doing weird things like eating typhods and snorting condoms on YouTube. So we need to take that energy and engage them as political subjects because they are, they have a political consciousness and they don't really conduct it quite weird, Stalinist way. I mean actually engage them as like genuine political subjects and teach them about the activist history globally and give them the tools and the understanding and historical knowledge to understand that they can affect social change. Number four, we need to build infrastructure outside the Labour Party. So as much as the Labour Party is a site of hope for people, every, all of you guys who are involved in campaigns, in media, in any organisation, you need to have a game plan. The whole Corbyn project goes tits up. So there's a lot of people out there with a lot of power that are going to try and scandal it. So we need to have a game plan so that the holds of crisis are not taken by the right if that's how stuff goes. So it should be honest, it's kind of looking that way. And fifth, we need to get ready for the fact that there's a lot of people out there that are ramping up for war. When Trump pulling out of the Iran deal with, you know, all of these kind of with mad men like Bolton in the White House right now, we need to make sure that we are ready for the fact that there are people there looking to get an Iraq mark too. We can't do what we did last time. We can't just wait for it to kind of overwhelm us.  And I think that that's what's going to help, you know, prevent a catastrophic war. So not to end this on a review note, but war is coming and we need to be ready. But yeah, so as grim as that might sound, I want me to take you back to that hope and that feeling of like feeling that everyone was laughing at us and we ignored them and went into the communities and organized and we achieved what we was told was unachievable. So always be bolder than you're told you can be, always be bolder than you think you can be. And I absolutely believe that we have so much unlock talent in this country.


Hi, what's up guys?  I lost like $14,000 on OCGN So I'm gonna kind of talk about all that stuff But before I get into the actual trading of the day I want to talk about How I kind of prepped for the day what I did the day before because as you guys know your process for the day Starts the day before so today's a Monday right today's a Monday and yesterday was Sunday Super Bowl Sunday Congrats, Tom Brady fucking sickening cat So let me explain what I did yesterday right so yesterday I was at a little bit of a Super Bowl party with a couple friends. We're drinking. We're all hanging out and you know the game ended around like I think 10 or 11 Eastern time and You know, I said to myself like my brother and his friend They bet a hundred grand on the game and they won All of a sudden they're a hundred grand richer and they wanted to go party and for me I didn't really feel like partying because I just want to get home early and I want to wake up and trade One days were my days Mondays are my busiest days in the markets. I wake up early and trade I do these YouTube lives. I get on a bunch of calls for MIC, so I really didn't feel like being hungover today so I was a good boy and I left the party Around midnight. I got home and I passed out and To my surprise at 3 a.m My brother and all of our drunken friends walked right into the apartment Started blasting music and all of a sudden I started to wake up after three hours of sleep and I was Here I am leaving the party early to go to bed early And then these guys go partying they go clubbing and then they come back and they start blasting all the music And I'm just like shit man. Maybe I should have just gone to the party So I was a little bit cranky this morning. I woke up and I started to watch the new podcast It's not that's gonna be a release soon. It's a podcast with dr. On and woody They talk about the frequently asked questions about date trading, but I started watching that 4 a.m. 5 a.m. Right and everyone leaves and all of a sudden I pass out in front of my computer, right? So all of a sudden I'm like drooling on my computer like this and I'm hearing my phone start to vibrate and all of a sudden It's 8 30 in the morning So I left the party early to sleep early and to be good and wake up early and prep for the morning instead I left the party early 3 a.m.  So already this morning. You could see that my process was kind of wet I wasn't prepped properly. I wasn't awake early. I didn't get enough sleep, right? So already from the beginning I knew that they was very dangerous day just for myself There could have been a bunch of easy plays But I know that based on what happened last night that everything was kind of screwed up for me So this is life. It happens. I tried to be perfect yesterday and life through a curveball All my friends got drunk they partied. They had a good time. They came back.  So that was my process for the day. I come into the morning and I was looking at the top gainers There was a couple low-hanging fruit like AAMD. There was a couple stocks. I ran off Friday They were kind of gaffin up today LIZI was one of them. There's SINO was like another one So there was pretty much decent plays, but then there was this one One stock that took everyone's attention. OCGF and the way that we explain the stock guys is we use an analogy called the hot chick So this is the girl at the bar that's wearing pretty much no clothes He's looking hot and all the guys want to talk to and most of the time The hot chick never works out because too many guys are giving her attention And she's having none of it. She's just getting everyone's money from their drinks and she's having none of it right so oftentimes These hot chicks these hot stocks are the hardest stocks to trade of the day because they have so much attention, right? So at MIC we like to focus on the stocks that people aren't talking about the stocks I don't have attention the stocks that are easier on the trade, right? So I started off my morning really well. I Shorted some game stuff today. I shorted some AME. I shorted another game through BSQR today I was really well and all of a sudden like my profits started adding up I was up like 10 or 15 Even maybe even $20,000 on the day and I'm thinking to myself.  And the problem with today's hot chick was that it was also easy to borrow, right? So as a short seller there is a couple warning flags that we have to be careful of so take notes right here guys If the stock is easy to borrow it has a high probability of squeezing if a stock has SSR It has a high probability of squeezing if the stock is a low float It has a high probability of squeezing if the stock has all three combined you're fucked, right?  And that's kind of what's been happening. So I Started shorting and the difference with OCGN and a lot of these other stocks is it was kind of conforming to the patterns that we like To see right we like to see rejections a whole and a half dollar marks We like to see pushes into key resistance areas and then stuff moves right back down on OCGN the stock Had its parabolic to 14 Came back down to like I would say 10 50 11 and then start to bounce Here I am guys here. I am starting to short around I think in my head. Okay. It just hit 14. It came down to 10. It's at the middle of the range around 12 I'm gonna start shorting right and the way that I was shorting this stock today guys Is I was using my 30% rule so we have videos on this and if you guys don't know I'm gonna briefly explain it The 30% rule means that if a stock is above VWAP, I am only allowed to use 30% of my max size So if I have a thousand shares Max size This is a rule that I created with my trading coach back in the day Brett steambarger and this was because If I stop out 30% of my size rather than 100% of my size not only am I not shell shocked not only is my loss small But I have the powder I have the money to be able to attack when it turns and this has been an Incremental rule in my trading. I know a lot of members in MIC are using this rule as well to help their trading as well So today I was short the 30% rule at $12 and my thought process was if this stock pushes towards 1250 the half dollar mark They're probably gonna push it and sell it off right and that's exactly what happened So they push it towards 1250 they sold it off And I was mentioning to the guys in the room that the stock had to break 1050 to create more downside. So my plan was this 30% size at $12 add to 50% size if 11 broke and add to a hundred percent size So now I had a plan and what was my stop? 1265 Now the stock went to 11 and it started holding 11 and I'm like, okay shit Okay, I'll go 50% size. No big deal. It's just And then all of a sudden Volume comes in it goes from 11 to 1150 to 12 to 1250 And at this point, I have a hard stop in at 1265. I guess stopped out. It goes to 13 It hits 13 boom right back down to 1150 and I'm like, oh my god I just cover the top.  So now I get emotional Now I tell myself, okay.  I'm reshorting now Here I am reshorting at 12 and now my plan is okay. If it hits 13, I'm gonna stop out So now it's at 12.   Yeah, I lost it But I'm still up for grand on the day and if I go back and think about it for grand on the day It's a million dollars a year guys.  Why am I upset? Sure? I wish I was still up 14 grand. I mean I was I wish I was still up 20 grand But the truth of the matter is like an extra ten thousand dollars isn't really gonna change my life guys So why the hell am I here complaining or why am I upset when I still make $40,000 on pay guys? And that's just the thing is trading is very competitive. I am in a constant competition with myself So I feel like if I lost that money But the truth of the matter is I managed my risk Stuff to my plan. Yes.  I use my padding in the morning I use my cushion in the morning to give me a false sense of confidence and it's all good You know, I've been doing very well on the year so far guys We're at like February 14 February 15 or some shit and I'm already up half a million dollars on the year You know last year I made a million dollars in the full year and in two months. I'm already at half that Now I'm not sending any arbitrary targets.  So although I lost $14,000 in OCGN today I still walked away green because I had so many other trades that added up I posted those trades in the chart recap channel for members and that's basically it So I want to kind of open it up to a brief Q&A now So if you guys have any questions leave it here Additionally, the number one question so I get a lot of DMs over the weekend guys I guess a lot of people start watching our YouTube videos over the weekend and they start to DM me and all this stuff And the number one DM I got over the weekend was do you think this market is gonna continue? Do you think this market is gonna end and you know my honest answer is guys? I think we're just getting started man. I think we're really just getting started. This has been the biggest inflow of Money entering the stock market in what seems like history You know the government is printing trillions of dollars and because everything else is closed those trillions Are coming right back into the stock market. There's so much uneducated money There's so much money entering the market.   I am now making seven figures a year So wouldn't you want to get started as early as possible so that you have the biggest advantage possible? When I started trading my season exists now because of MIC traders are fighting consistency in less than six months Some traders that put in the work like they 45 days so If you want to enter the market, you don't know what you're doing. Maybe you're investing in dogecoin Maybe you're investing in GameStop.  So Let's open up to a Q&A guys for about five minutes And then I'm gonna get back to work like I said Mondays are my Busiest day so I have a lot of back-end stuff to catch up on and a lot of p.m.  So When there's so many plays how do you filter things down? I'm having a hard time choosing which stocks to play it seems like I make a plan for stocks That lines never hit that's a fantastic question. So for me, I like to narrow it down Most of the time if I try to trade more than three or four stocks on the day I end up losing and the reason why is because I don't like to split up my focus I like to trade the best stocks only and take it from there And how do you kind of narrow it down was the question to be honest for me? It's about screen time. It's about knowing which stocks that It's about knowing which stocks You are comfortable with it's about knowing which stocks you constantly profit on for me when I'm trading in the morning I like to focus on stocks that are under the market and looking to short them on a bounce So what I like to do is that there's five stocks moving and three of them are under the web Those three take my top priority, but oftentimes it's screen time after being a trader for seven years You learn which stocks to trade and which stocks to avoid and now as I'm recording this video guys OCGN is at 1350 I stopped out at 1350 had I held Had I've been stubborn had I not managed my risk had I just prayed had I just broken all the rules You know what I would have not been up four thousand I would have been down twenty five thousand dollars on the days Do you know what as upset as I was 20 minutes ago?   I would have lost an additional $25,000 You know what $4,000 sounds pretty fucking good to me today man So any questions guys any questions me does this all make sense Please if this is making sense leave a like on Let me know that this is you guys are getting it, right? This is the day and the age of the pump-and-ups. There's so much people there's so many Pump-and-up rooms. There's so many scam rooms just pumping garbage and what you realize is day one. They pump it Day two they forget it.   I'm not perfect. I don't think I'm perfect When I do screw up, I'm gonna be here Explained to you. I'm gonna try to improve on it. These videos are like game footage You know how professional athletes watch footage of their games and replay the footage to see where they What they did right and what they did wrong I go back to these videos and this is kind of like my video diary What I did right and what I did wrong and what I can improve on and today I Shorted the hot chick that was easy to borrow. I Traded too many times. I went back to the well too many times But you know what stuck to my process I stuck to my rules and because I stopped out I walked away green on this.  Okay, if you are not using hard stops in your trading You will not make it trading It is very easy to make money in stock or stock market. It is very hard to keep it in your pocket Hard stops and zombie rules made me a millionaire and they will make you a millionaire too Guys, please leave a comment with one lesson that you learned on the video I'm gonna go back. I'm gonna reply and maybe I'll pick someone to win a free month or a free t-shirt or Free phone call or whatever. So appreciate you guys And if you guys have any question about trading text us to one three four five eight five nine nine seven I'm gonna head back answer some questions And I'm going to short the shit out of OCG and if it Confirms and if it shows us and there is a reason to short it because today.  So maybe I'll wear that lucky shirt that I made 300 grand on tomorrow So we'll see and if it's a crazy day tomorrow, I'll see you on Bowser's Instagram live So have a good day and I'll see you guys back in the room


Hello everyone and welcome back to the attic. Apologies for that slight delay that it had only to do with us, with our production team, nothing to do with our keynote speaker that's been patiently waiting. So we're so happy to have him here to talk to us about foundations of data teams. A successful data project needs to be built on solid foundations to tell us just how important this is and how to do this reliable. We have with us Jesse Anderson, managing director of Big Data Institute. Jesse, welcome. Welcome to Big Things conference and apologies for the delay. Looking forward to listening to you. So we'll catch up on that, on those minutes. Whenever you're ready. I'm ready. Thank you again. Thank you for an introduction. Thank you for taking the time to be with me. So let's try and make this more interactive. Let's try to be use zoom for what it's good for. I have the chat open. Tell me, are you a manager? Put a yes in the in the chat. If you're a manager, if you're an individual contributor watching this, put an N and that will help me get to know who you are and so that we can talk about this accordingly. So what we're going to talk about are the foundations of data teams. And here's our itinerary for this talk. We're going to be talking about houses. And you may not be thinking about if you're in a big data conference, a house, but we're going to be talking about that as a metaphor. And I'll explain what that metaphor means. Then we're going to talk about disclosure. What does it mean to disclose problems? Who's responsible for that? Then we'll talk about the data teams themselves. What does it look like when we do or we don't have that data team? Finally, we'll talk about the implications. There are very specific implications for this. And I think it's really important that you know that. So just put that in the chat and I'll be able to see that. So sometimes it's really implicit about what we want versus what we get. Sometimes we don't actually state this. Sometimes it's kind of implied where when somebody says, I want data, they don't specifically say, I need data in this particular system, and I need it in this format. They kind of say, well, you need to go figure that out. It's implicit in that.  And so sometimes when we get that asked, sometimes when we get that asked from maybe our business, from our whomever, sometimes what we're focused on is that exterior, that cosmetic, that you can see that picture there on the right. As you look at that picture on the right, seems like it's Italy to me and looks just looks like Italy. And it's incredibly beautiful. The houses are all beautiful. But as we look at those beautiful houses, we don't think, Oh my goodness, what kind of foundation do they have? And I wonder who engineered and architected that. What we think about is that house looks beautiful. I'd love to live there. I'd love to have that view. But there's all kinds of things there. Their houses literally hanging on the hillside. But so there had to be some level of engineering that has to go into that. But we as consumers of that house, we focus on that exterior focus on the cosmetic. So in this kind of metaphor, what we're going to be focused on is houses. The houses are the value that we create as data engineers. So what kind of value do we create as data engineers? It's our house. And we'll kind of use that metaphor throughout. And then our construction. How do we go about creating that value? And this is what we need to do. We need to have that be constructed. We need to have something that somebody built, somebody engineered, somebody put effort into saying, this is how the house should be built. And the responsibility for that construction is actually us as data teams. We need to be doing that. So we'll be talking about what that construction means for us as data teams. A lot of times our focus is on the facade. And as you look at this picture, you'll see a movie lot. If you ever seen how movies are made, what happens is they will do what's called an exterior or a facade. And somebody will stand in front of, in this case, Pete's joke shop. And all you see on the camera is that window and that door. But could somebody actually live there? No, of course not. It's just a facade. It's just here is literally nothing. And we're missing the complete rest of the structure. Oftentimes when we are working with data teams or we're creating our data teams, we're so focused on that facade, we're so focused on that model that we forget the rest of the structure. And this can be a huge problem, which we'll get more into later. But this is something that is commonly people fall into, especially data scientists, especially business leaders who've really bought into that notion that you only need data scientists. The reality is that we need all of the teams. We need all of the data teams. Otherwise, if we just have that data science, that's just the facade. If we have the rest of our teams, then we're going to have the rest of the building. Somebody could actually live there. And this is that value being created. Other times, people will talk about foundations. They'll wonder, if we have a data team, do we just spin up that data team for three, four, six months? And then we say we don't need them anymore? The real question there is they're asking, do we need a foundation for these data teams? Or are they so transient that we don't need that? Here in this picture, we see what's called a yurt. And a yurt is really interesting because it's a type of house that doesn't need a foundation. It was created by nomadic peoples. What nomadic peoples means is that they don't stay in one place forever. In fact, they specifically created their teams, their houses, to be able to move. So they could pick that house up and they could move it elsewhere. But is that really what we need with data teams? Well, houses don't really need a foundation if you don't need it to stand for long. But data teams do need to stand for a long time. They aren't a six month thing. They aren't a one year thing. Therefore, this point onwards, that we are going to continue to have our data team. We are going to continue having that data team be a part of us. So what we have to do is we have to make sure that our foundation is solid. We have to actually create a foundation. We aren't nomadic data teams moving from one thing to the next. We have to build a solid foundation for them. And so we do. We do need a foundation because we want it to stand for a long time. So sometimes people will buy into this issue or this thought that, well, it's an easy renovation. I want data science and that's an easy thing. I'm just going to take hire a data scientist, plop them in and say, okay, we're ready to go. We've got that data scientist. Well, that isn't really the case. As you can see in this picture, here they're just doing something so simple as remodeling the outside of the building. But how many people did it take? There's all kinds of people. There's all kinds of scaffolding. So when we think about adding something like data science in, this isn't a simple addition. It's not a simple, easy renovation. Adding and these advanced analytics requires a lot. It requires more than sometimes, oftentimes what managers have been told, oftentimes what they've been seen. So rarely what we need to do is we need to see what actually has to happen. If we say I want data science, this is what actually has to happen. We're not just at this easy renovation. So this brings us to the question of disclosure. What does disclosure mean? Well, I know many of you are from around the world and oftentimes, at least in the US, we have these laws and these laws say, if you're going to sell a house, you have to disclose any problems. You actually have to say, I'm selling my house and my house has a problem with a roof. I know about it. You should know about it too. However, sometimes sellers don't actually want to disclose everything. It makes the value of their house drop. It makes it where they thought they could sell their house for 500,000 euros. Now they can only sell it for 100,000 euros because it's going 400,000 euros because it's going to cost 100,000 euros just for me to fix that route, for example, or it's going to cost that to fix the foundation. And oftentimes, depending on the country that you're in, this non-disclosure, this not telling of the problems actually has legal and monetary implications where if somebody doesn't actually say, hey, there was this problem with the house, you can go back and sue them. And you can say, you should have told me about these problems. Now I have to pay for them. And if you look at the image there on the right, this is the disclosure form for the state that I live in the U.S. And it actually says, here are the problems. If you don't say this, you will have this and this problem, failure to disclose will have these problems. So tying back to our data teams and our houses, who's responsible for this? Well, let's talk about that. Whose job is it to actually disclose problems on your teams, issues on the teams? Well, you can go through that list. Is it a vendor's job? Is it a management's job? Is it an individual contributor's job? Is it a book's job? Well, let's kind of go through each one of those. Is it a vendor's job? Do you remember how we were just talking about the issues with vendors or with the non-disclosure, where if they actually disclose and they tell you, hey, there's this problem, it actually makes their jobs difficult, their house worth less as it were. So what oftentimes vendors will do is they'll tell you it's easy. They'll actually tell you the opposite. They'll actually say, hey, I don't want to make it sound like it's too difficult. So I'm actually going to tell you the opposite and that's an issue. So vendors can't really trust the vendors to do that. It's going to make it so they can't sell. Is it up to management? Well, you're getting closer. Management needs to be able to say, hey, there's often this issue of they don't know what they don't know. They don't actually know that there was a problem. They don't actually know that you do need all the data teams. There can be lots of issues like that. Is it up to your individual contributors? Is it up to your data scientists and data engineers to say, hey, I'm just one person. I actually need more people. I need a foundation here to build on. Or is it books? Well, there's all sorts of books out there on data science. They range from rah, rah, rah data science of everybody's going to do data science and here's all kinds of value you can get. They don't really tell you, here's the work that you have to do. So there is some missing pieces of whose job it is. I mentioned this a bit earlier, but sometimes people, you'll actually hear from vendors and maybe you've even heard from vendors in this conference and they say, ah, don't worry about it. It's easy. This particular technology, my technology that I'm selling, everybody else's is difficult. Mine is easy. Mine is easy because I'm able to do this, this, and this for you. Well, is it really easy? Well, I would say some vendors are actually misleading in their disclosures. They're trying to sell you this house and they're going to say, hey, it's easy. You don't need that foundation. Don't need those data engineers. It's all easy, but is that the reality? Is that actually true? And I would say oftentimes those vendors are actually misleading in their disclosures. They're telling you something that isn't actually true. It is actually the opposite of what the industry sees, what we see in the field, and it's sad, quite frankly. So now let's talk about the data teams themselves. What do you need for data teams? So here we have a diagram of the three data teams we need. And sometimes when we talk to management, the managers will say, which one of these teams do I need? Just need one. I can just get by with data science, right? Or they've been told by somebody or they've read something or the focus of an entire book was you just need data science. Well, here's the issue. You actually need all three. Each one of these teams is equally important and they give a specific part of that value to being a part of a data team. And if we don't do this, we're going to have a problem. So in the next few slides, we're going to talk about, well, if you're missing one of these teams, what does it actually do? But each one of these teams, data science, data engineering, and operations, they form this triangle that is required. They all have to be there. So let's say we didn't have data science. What would happen? Well, let's say there is a foundation. As you can see in this picture, we have a foundation. It's more or less clean. I wouldn't say it's the cleanest thing, but no one could live there. Why can't anybody live in this place? Well, it's because there's no value being created. Without data science, I would go so far as to say, if you're not going to hire data science, if you're not going to do data science, what is the real value of what you've done through all of your data engineering or through operations? Because you can get to some level of value with the business intelligence. Definitely. We've been getting some level of value with them. But the maximum, the highest and best usage, the highest and best value possible is definitely when we have data science. They're kind of the cherry on top. If you think of that Sunday, that ice cream that you're eating, well, that cherry on top gives you that thing that you say, oh, yes, generating incredible value. So here, when we lack data science, the business doesn't get enough value created so nobody lives there. We have to have data science. But what happens when we don't have data engineers? That's a whole problem unto itself. As we can see in this picture, the lack of engineering in this house made it crumble. Maybe it was due to a large snowstorm, whatever happened. It was due to a lack of engineering. So likewise, in our data teams, when we don't have data engineers, the infrastructure, the data products are going to crumble because there is a lack of sound engineering. This is what always happens. This consistently happens. And we have different words for this. We have words such as technical debt. Well, in my experience, and I've worked with a lot of teams around the world on this, when there are just data scientists and there are no data engineers, the amount of technical debt that is created is significant. It's this huge weight that sits there on the roof and makes it crumble. And for you as managers, what this looks like is the team is far less able to actually be productive. They can't really do anything because they're always limited by that technical debt that you hear in the meetings and the stand-ups, for example, they say, I would really love to do X, but I can't. Or it's going to take too long. This is what it looks like when you don't have data engineers. You lack that sound, that infrastructure, that scalable infrastructure, and everything is always crumbling due to the technical debt. Likewise, when we have our operations, operations, when we lack it, we can see that in the picture. Hey, there's a foundation that hasn't crumbled. You could say that there's some amount of value being created. There's something, somebody lived there at some time. I wouldn't say they're living there now, but somebody lived there at some point. So without this operational excellence, the business can't use these data products. If they're just completely neglected, if they're messy, if they're unkempt, what happens is the business will never be able to trust them. I don't know if you've ever talked to a business person or the business user, and you talk to them about a data product, they say, it was so unusable, I had to create my own. I've talked to people who've had to do that. And it was because there was no operational excellence, that the data was so dirty. The data was, the infrastructure was always down. They could never wait for it. They could never use it. They could never be confident that it was ready to be used. This is a lack of operational excellence. And this very specifically will inhibit you from actually getting some usage out of this. Without operational excellence, you can do all this incredible data engineering, the most incredible models ever. But if it's not up and running, it can't generate value. You absolutely have to have operations too. As you can see now, you need all three of these. All three of these provide different levels of value. So what's the implication here? So maybe you have, you're about to start a team. Maybe you've created a team already and you're starting to see some of the issues of your foundation. Well, guess what? It's always better to put the effort into a solid foundation initially. Always better. And by doing this, we're able to get into this solid foundation. We're able to say, hey, as you can see in this picture, we're building a skyscraper here. And we should put the effort into this. As you can see, there's a lot of rebar. There's a lot of concrete that's going into this foundation. They are putting a significant amount of time, money, and effort into this. And they're saying, if we make this foundation right, we will get it right. We will be able to build on this and we'll be able to build a building that stays up forever or for a long period of time. But if we don't, there's big problems. If we don't build that solid foundation, it is going to cost significantly more to go back and fix it later. Significantly more. And this is what this looks like. There is a building in San Francisco. It's called the Millennium Tower. You may not have heard of it, but here's what happened. They had a problem with their foundation. Now, there's fingers pointing everywhere of whose fault it was. And that's interesting unto itself, a point being they had a problem with their foundation. And this tower was not a cheap tower. This was $750 million US and a pretty significant amount of money. The actual apartments that were in there, penthouses, that sort of thing, these were luxury penthouses. These were very, very expensive. And so a lot of wealthy people lived in this tower. Well, what happened? As you can see, I've taken the liberty of doing some screenshots of some headlines from it where they said, well, there's a $200 million lawsuit to go back and fix it. And to say, by not creating the solid foundation, you cost us $200 million. And oh, by the way, in addition to that $200 million, it's going to cost $100 million just to fix this foundation. It's a big problem. And you can see that from the pictures here.  So who knows what the actual problem or whose fault it was. But suffice it to say, there was a problem with the foundation. And this problem with the foundation was significant. So let's talk about this in terms of your teams. Well, would you rather create your team the right way? Would you rather put the right foundation in? Or would you rather go back and spend $300 million to fix it? And this probably $300 million is probably on the low end. It's probably going to cost even more for them to fix this right. So that is some pretty significant problems.  What you need to go back and talk about and think about is if we don't make this solid foundation, you have to do it no matter what. As we talked about, we're not in yurts. We actually need a solid foundation. We need to put a significant amount of money and time into our foundation. And if we don't do that, if we don't get the right people, the right teams in place, we're going to have to go back and fix it later. And fixing it later when we're, for example, missing a data engineering team, it means, and I've experienced this personally first hand, it doesn't mean we spend a week or two cleaning up some of the data scientist code. It actually means we spend a year fixing data scientist code because there was no data engineering place to say, hey, that infrastructure that you did, that code that you did is not good. The way you wrote that, we need to do it this way. We need to do it this way instead. Or operationally, experience that too. There's no operations in place. The business starts having trouble. The business starts losing money because you can't be confident in your infrastructure always being ready. So there are definite issues there. Likewise with data science. Well, data science is really that facade, that last piece that we need. So for missing that, it's going to be more difficult to add this later. So we really, really have to make sure that I would say that two key ones, two key initial ones, is data engineering and operations definitely. So why would we want to do this? Let's say we have an existing team. What does this look like? And so I wanted to create a visualization for you as managers, maybe as tech leads or what have you to see what exactly it looks like and perhaps even explain what you're seeing right now to put some words and visualizations of what you've been seeing. So we have two lines. We have a red line and a blue line. One, we have the blue line with a solid foundation and we have the red line with where we're lacking a foundation. So what happens when teams lack a foundation, they'll get to a certain point and they'll just crash. As you can see, they'll get to a certain point and crash. And what will happen is they'll work, work, work, work, get to a certain level of either the infrastructure dies or they're missing the right people or they're never able to build on that solid foundation and leverage that. They're always trying to go back up and down and trying to get back to where they were. It's really sad. It's really, frankly, unfair to the teams that they're being set up for failure like this. However, if we look at that blue, that's that team with a solid foundation, they will gradually go up and they'll get to new levels and then they'll kind of level out, go up to a new level of complexity, level out. Notice there's no going down. There's no crashing. It's because they built a solid foundation each time and they're able to build on that foundation. And as you can see, once the team gets into more and more complex things, by building on that solid foundation, they don't have this crash. And this is really what's key.  And then they crash and there's no productivity. That what you were told initially would take a month, now take six months. That's what a crash looks like. Whereas when you do have these solid foundations and these right teams in place, then you'll be able to build on top of that, build on the next level, build on to the next level. And you will have a significantly more productive team as a direct result. So if it isn't clear already, it's always more important to have a ounce of prevention. You may have heard the term or the saying an ounce of prevention is worth a pound of cure. You may not know what ounces since you're in there, but maybe it's a milligram of prevention is worth a kilogram of cure, if you were to put it in metric terms. Well in data teams, I say it's worth a milligram of prevention is worth hundreds of kilograms of cure. If you just put the effort in initially, you're going to save yourself so much on the back end, so much afterwards. And so what I want you to take away from this is it's always possible to fix your foundations. Always possible to go back and say we are going to fix this, is going to be costly, and the longer you wait, the more expensive it's going to be, but it's always possible. So do take that, those of you with existing teams, you can fix them, the longer you wait, the more difficult it's going to be, and the more technical debt. So what I want you, one thing to really take away, really to internalize on this is this is not saying this is purely a technical issue. That's what happens sometimes. People say it was an issue of spark, it was an issue with Kafka. Well, there may be issues with that, but the key issue was it was both technical and organizational, and you have to fix them both at the same time. So this ounce of prevention is to set yourselves up organizationally, so that you can leverage the technologies correctly. And that's really key. So although I don't talk specifically about set up organizational, I just wrote a book called Data Teams. And in it, I share more about what each team does, what each person on that team should be, what a data engineer is, what a data scientist should be, what an operations person should be. And that perhaps some of the parts I'm most proud of is that a good portion of the book is actually talking about how do data teams actually interface with the business. This is part of how we create that value. So once we get that solid foundation, then we need to be creating that house, we need to be able to create that house that we can live in so that the business can actually generate value with our data products. This is really key. Other things I'm really proud of is for those of you with existing teams where you're not understanding what's happening, I have an entire chapter in there talking about this is what you need to do, how to fix that. So I would encourage you to read that. There's a website for it. It's called datateams.io. So with that, I'd like to thank you. And I really appreciate you spending some time with me and attending this keynote session. Thank you. Thank you so much, Jesse. Excellent. Very interesting. And you answer a lot of the questions. We have time for a couple of them. They ask you, do you need a chief analytics officer or chief data officer? Can we have both? Should we have both? That's an interesting question. It's actually one I talk about in the book. Who should the data teams be under? So to give a kind of an adjacent answer before I answer that question directly, one of the issues is if you have your data science and your data engineering in separate parts of the org and that you have to go all the way up to the CPO for resolving any issues with resources, that's going to be a problem. So what companies are trying to do is they're trying to centralize their data teams under the same chief level officer of the company. So to that question of CDO versus CAO, I haven't seen anybody have both. It seems like it's a one or the other. And it also seems like it's a how the company or how the data teams came out. Was it chiefly a data science, really data science focused? If they're really data science focused organization, I found it's a chief analytics officer. If it's a really data engineering kind of engineering heavy organization, I found it's a CDO. But at the same time, what will happen is that CDO, that CAO, they'll be able to do the job. They may not be a strong on one part of the other. And they'll be relying on strong people, really good people on both sides to be able to lean on and say, if they aren't as good on the data science, lean on the data science manager, they aren't as good on the data engineering. But I think really what is key for CDOs and chief analytics officers is to realize that. One thing that I would suggest is I actually have an interview in the book with the chief analytics officers for Stitchfix. And we go through that and talk about how they have their team set up. Excellent. We're gonna have to read the book. I already read some reviews through Twitter about the book and people just highlight all of it. Everything is so interesting. So congratulations on that. We have time for a very quick question. If you promise a quick answer, Jesse, they ask you, one of the common reasons why data engineering teams fail. If you can pinpoint at least two or three quick mistakes, quickly some of the most common mistakes, you would say. The first and foremost ones is having DBAs as your data engineers. DBAs, in my definition, are not data engineers. They have to be software engineers. So that's one. Okay. What companies will do is they will take their data warehouse team, say your data engineers, now you're going to do that big data project to arrest the people failure. The other one is to not give the data engineers the resources to learn these new technologies. These new technologies are difficult, no matter what your vendors say, and they do need the time and resources to learn. Okay. Excellent. Well, thank you so much. I bet we can read a bit more on your book, Data Teams, that came out in September, last September, if I'm not mistaken. Actually, I think it came out on my birthday, if it's on the 23rd. So I wrote it for you. You just didn't know it yet, and we didn't know each other yet. Okay. Thank you so much. I recommend everybody gets the book and obviously listens to all of your talks and follow you around. Very interesting. Thank you so much for point pointing that we need data scientists, data engineers, and operations mainly. So, Jesse Anderson, thank you so much for being with us today in this edition, the ninth edition of Big Things Conference, and we hope to see you very soon. Stay around in the attic for the last of our keynote speakers today in a minute.


Congratulations to all of the Navy's newest Chief Petty Officers and to all the family, friends and shipmates who helped get you to this moment. This is a transformational day, one you will remember with pride. The journey you took to get here was tough. You were tempered, you were tested, and you were accepted. You've earned your anchors. But now, the real challenge begins. You have joined the finest institution in the world, the Chief's mess of our great Navy. By institution, I do not mean a special space, color device, or a set of traditions, but the sum total of acts our Chiefs undertake every single day to make sure our Navy remains the finest fighting force in the world. Even the briefest scan of history shows that our Chiefs are sailors of action. Some, like Medal of Honor winners Oscar Peterson and Peter Tomic, gave their lives for their sailors. Others like Dick Turpin and April Beldo broke through barriers to make our Navy stronger. But there is something even more powerful than their individual examples. Our Navy's 245-year history of success and battle. Our Navy relies on the strength of the mess. We just commemorated the 75th anniversary of our victory in the Second World War. The line of heroes that inspire us from that struggle span all the ranks and rates. Sailors like Gunners-Mate, Third Class Paul Carr, and Mesa Tenant First Class Doris Miller stand alongside others like Commander Ernest Evans and Commander Howard Gilmore. All showed great courage under fire. All gave their life for our country. But what also ties them together is that they were all trained and they were mentored and inspired by our Chief Petty officers. And those Chiefs would probably tell you they weren't looking for credit. They were simply focused on the actions needed to get the mission done. They were focused on making our Navy the most lethal fighting force in the world. And they were focused on creating warriors, the sailors and officers whose action would bring America victory at sea. Today we face another great power competition, one that tests us in different ways, but one that still has potential for devastating consequences. The margins of victory at sea are razor thin. We've got to be ready. So I charge all Chiefs to think about your mess as a living, breathing institution, one that must be renewed every morning. An institution that rises to the high standards of those who came before you and one that leaves our Navy stronger. A place where you re-earn your anchors every single day and treasure that incredible gift of being called the Chief. We must take a moment to honor those who poured their time, their energy and their faith into each one of you. To all the family, friends and shipmates of our newest Chiefs, thank you. Our Navy appreciates your many years of sacrifice and service. This day belongs to you as well. Caring for the legacy of those who came before you will test you and will require all the wisdom and strength that brought you to this day. The demands placed on you will be tough. I have high expectations of our Chief Petty officers as do the sailors you will serve and lead, but I'm confident that you will meet this challenge with humility and with determination. Draw strength from the creed and from your fellow Chiefs. Indoor adversity with focused determination make the most of every day, leading our sailors and officers to fulfill the promise of their potential. Congratulations Chiefs, now anchor up.


So let's take something like I'll let's go to my money put one of my playlists Music here's some popular music that I enjoyed now look at this guy I am creating moments from popular music that I enjoy in a playlist that start at exactly the chorus or The cool guitar solo that I really enjoy you cannot do this on YouTube