So, welcome back in the last class we were looking at acid-base equilibria and if you consider this as a generic reaction for acid-base equilibria, you have 2 acids here HA and BH plus which is the conjugate acid of this base. So, I told you understanding the relative acidities of both of these is very important. So, to predict the relative acidities there are 2 guiding principles you can use. For neutral acids more stable conjugate base implies stronger acid, for cationic acids more stable acid would be the weaker acid. And then we had looked at all of these factors which affect acid strength, so we had looked at solvent, a solvent which solvates the ion more. So, in the case of a neutral acid if the ion is more solvated that means you have a better acid whereas for a charged acid if the acid is more solvated it would be a weaker acid. Then we had looked at electronegativity where if you have the acid Hx, so greater the electronegativity of X better would be the acidity. Then we had looked at examples as to where resonance plays an important role in increasing the acidity. If you have a conjugate base which can be stabilized by resonance then you see an improvement in acidity. We had also looked at bond strength so within a group, so within a group what you see is as the bond strength decreases the acidity increases. So, if you compare Hx where X are helides what you would see is Hi would be greater than Hf. And I told you that you can use this to compare only when you have atoms within a particular group. Then we had looked at electrostatic effect where if you have your conjugate base say you have, so if you have a positively charged species here let us say R+, that would stabilize this conjugate base. Then we had looked at hybridization where sp would be more acidic than sp2 would be more acidic than sp3. And the last thing we had seen is stabilization due to aromaticity which leads to improvement of acidity. So, if the conjugate base is stabilized by aromaticity you see an increase in acidity or lowering of pKa. So we had looked at all of these factors in the previous class. So now what we look at is the catalysis by acids and bases. We would be looking mainly at Bronsted acid base catalysis. So Bronsted acid base catalysis means you have a proton or a hydroxide. So proton generally in the form of H3O+, or the protonated solvent that you are working with that is what would be important and the hydroxide. And here what happens is the proton or hydroxide due to interaction with the reactant lowers the energy of the transition state for the reaction and thereby you have an accelerated reaction. So it acts as a catalyst and of course at the end of the reaction your proton or hydroxide is regenerated. What you observe is so these are called Bronsted acid catalyzed reactions. What you would see is there will also be examples where you will have the acid or base being consumed.  So in these cases these reactions are called acid or base promoted reactions. They cannot be called catalyzed because your acid or base is not regenerated at the end. So for classification they are classified as specific catalysis and general catalysis. So what do each of these terms mean? Let us look at each of them in a little detail. So the first is specific catalysis. Now many people get confused with the terms specific and general. What you need to remember is in specific catalysis proton transfer occurs before the rate determining step. So proton transfer is not involved in the rate determining step. Proton transfer occurs before the rate determining step. So in other words the proton transfer is very, very fast. Now what exactly is a specific acid? Specific acid the term itself means protonated form of reaction solvent. So it does not matter what acid you are adding in the reaction, you are only talking about the protonated solvent as the factor which improves or which shows up in the reaction kinetics equation. So what do you mean by protonated form of reaction solvent? If you are looking at water as your reaction solvent the protonated form would be of course H3O+. That is the specific acid. If you are looking at doing a reaction in DMSO, this is the structure of DMSO. This protonated form is your specific acid. If you are talking about doing a reaction in acetonitrile this is your specific acid. So again I want to emphasize this specific acid is the protonated form of the reaction solvent. You can add any other acid in the reaction, you can add some small amount of acetic acid, it does not matter. What matters is only the protonated form of the reaction solvent. It is very, very specific to only the protonated form of the solvent. Again specific base is the conjugate base of the reaction solvent not any other external base that you are adding. So if you consider water the conjugate base would be OH-. If you are looking at DMSO the conjugate base would be this carbanion here. If you are looking at acetonitrile this is the base that you are talking about. So these are all the specific bases that you are talking about when you do the reaction in these particular solvents. Now let us try to get a deeper understanding of what it means that no other concentration of acid or base has an impact on the reaction rate and it is only the protonated form of the reaction solvent. So to keep it simple let us look at a reaction in water. I have just chosen water for simplicity. You can choose any other solvent and it would boil down to the same kinetic expression. So let us give this reaction so you have your reactant being interacting with the protonated form of water which is your specific acid. So you have H3O plus giving you the protonated reactant. The next step conversion of the reactant to the product is your rate determining step. So this is the slow step and the protonation takes place fast and all these steps are also fast. So this is a typical expression that you would see for specific acid catalysis. I repeat for specific acid catalysis proton transfer is fast. So it occurs before the rate determining step alright and the reaction rate only depends on the protonated solvent. In this case it would be H3O plus. Now let us derive the kinetic expression for this. So if you remember when we were studying kinetics we were looking at rate loss. So when we were looking at rate loss we had done derivation of rate loss for complex reactions. So let us try to derive the rate law for this. So in this case to simplify it we will just start from the rate determining step. So the rate for the reaction would be given by K which is the rate constant for this process into concentration of Rh plus right. So based on what we had studied for rate loss this is the rate expression. Now what we usually do is we move back and try to express Rh plus in terms of Rn H3O plus. So I will give you a hint I will give you the final expression. So this is what the rate dp by dt the rate expression is given by this where in the numerator you have the rate constant K which is this concentration of R concentration of H3O plus and in the denominator the term that you have is the acid dissociation constant of Rh plus alright. So with this information I want you to look at your screen carefully and try to derive this from this form that is given here. So I will ask you to press the pause button and do this derivation yourself before you start working it out with me. As I have told you again and again the best way to learn is to practice yourself. Once you practice you can check your answers by comparing with me. By practicing you will also come to know what the mistakes it is that you are making. So go ahead and try to work out this derivation. So you can check your answers now. So by definition the dissociation constant Ka of Rh plus deals with this equation. So you are looking at Rh plus plus water giving you R plus H3O plus right and this could be the K equilibrium for this process. So now the K equilibrium for this process is given by R concentration of H3O plus divided by Rh plus we had done this and I had told you if you take water on the left side what you get would be the Ka or dissociation constant would be given by Rh 3O plus divided by Rh plus. So in other words if I were to write Rh plus in terms of these it would be concentration of Rh plus will be equal to R into H3O plus divided by Ka of Rh plus right. So now if I plug in this value of Rh plus in this equation let us call this equation 1 you would get rate is equal to dp by dt is equal to Kr into H3O plus divided by Kar H plus. So now we have derived the rate law for this reaction which is catalyzed by an acid in which the proton transfer step is fast and occurs before the rate determining step. So what do you see here now when you look at the rate law the acid dissociation constant is a constant for the particular acid Rh plus concentration of R is your reactant. So what you would see is you do not have any term corresponding to the acid. So what you have is essentially you can say this as K observed it only depends on concentration of the protonated solvent which is H3O plus here. Now one might argue like what if I add a small amount of acetic acid to this if I add acetic acid you would say that instead of H3O plus maybe I will have the acetic acid there and it would be something different. So based on the definition of specific acid catalysis in this case you have specific acid catalysis because the rate only depends on concentration of H plus which in turn depends on the pH of the reaction medium. So if you maintain the pH of the reaction medium you essentially are maintaining the reaction rate. So now if you argue with me that I am adding now a little acetic acid. So now we have added an additional term which is HK right. So if you are adding acetic acid the question is now will this still follow specific acid catalysis. So now you need to remember that this step is again fast all of these are fast. So what we have is based on the original definition you have proton transfer occurring before the rate determining step. So by definition this should follow specific acid catalysis. But now let us mathematically derive to see is it true. So like before you would write the rate would be given by K into concentration of Rh plus because that is what is involved in the rate determining step right. A- is just a byproduct of the first reaction so it does not show up. So you have the rate determined by concentration of Rh plus. Now let us see if we can write Rh plus in terms of R and HA. Remember you also have water in the medium. So it is not just the HA disintegrating to H plus and A minus it is slightly more involved than that. So you need to introduce water here. So this is the final expression where you can talk about the rate in terms of the first equilibrium which is this. So this is K equilibrium the dissociation constant of the acid HA. So again let us try to derive this. I will ask you to derive this first yourself.  So let us see if you have the answer. So here again let us first try to write it in terms of the equilibrium constant. So the equilibrium constant for the reaction K equilibrium is given by Rh plus times A minus divided by R into HA correct. So in terms of this what you would have is you will have Rh plus equal to K equilibrium into R into HA divided by A minus. So that takes care of these two terms and this we have already. Now we would like to write HA by A minus. This ratio is determined by the acid dissociation of HA. So KAHA so the equation that you are looking at is HA plus water giving you A minus plus H3O plus right. This is what gives you the acid dissociation of the acid HA. So now the KAH value is given by A minus into H3O plus divided by HA remember the concentration of water is included in the term KAH. So now that you have this term what you get is you get the ratio of HA by A minus is equal to H3O plus divided by KAH. So if I plug in the value of Rh plus and this HA by A minus into this equation what I will get is the final equation that you have here. So here you can substitute for K equilibrium R and HA over A minus is given by H3O plus by KAHA. Now what do you observe here? What you observe here again is despite the fact that you have added an external base here again it reduces to the earlier form where you have K observed into R. So it essentially depends again on the pH of the reaction and what was your reaction solvent water and protonated form of water is H3O plus. So we have mathematically derived here that the specific acid catalysis is seen whenever you have a reaction where the proton transfer occurs quickly before the rate determining step. So now that you have an understanding of specific acid catalysis what I want you to do is I want you to do the same derivation for specific base catalysis and here again what we would be looking at is we would be looking at the rate would be given as this is K here again the base would deprotonate much faster as compared to the rate determining step. So the rate is given by K into concentration of R minus alright and now you can write R minus in terms of the base and just like we had done for the previous slide where we had added acetic acid in water here again we have added a base in water. So this is what your final expression will come like. So we are again writing it in terms of acid dissociation constant of Rh into concentration of Rh and H3O plus. So you can go ahead and derive this quickly now that we have seen the earlier example this derivation must be quite quick for you to do. So we will quickly go ahead and do this derivation. So here what you have is the rate of formation of the product is given by this expression. So when you look at the dissociation of Rh you are looking at Rh plus water giving you R minus plus H3O plus correct. So now Ka of Rh would be given by R minus concentration into H3O plus concentration in the denominator you have Rh water as I said is included in this. So now you can write R minus so R minus is equal to Ka Rh into Rh divided by H3O plus. So you plug it into the equation above so if you plug this value into this equation you will get the final equation for the rate. So here again you would see that the rate does not depend at all on the concentration of the base. So we have seen how by deriving the rate law again we are connecting to a concept we had learned earlier which is deriving rate laws for reactions. So when we derive these rate laws what we see is that when you have specific acid or specific base catalysis where proton transfer occurs quickly before the rate determining step you do not see a dependence on concentration of the acid or base. The kinetics depends only on specific acid or specific base which is the protonated solvent okay. So now if you look at so if you have understood this concept I will ask you to just make a very simple plot. So what will the plot of K observed versus concentration of HA where HA is the acid that you are adding say in water which is the solvent. So what will this plot look for when you are doing specific acid catalysis alright. I will repeat the question is there on your screen so you can press the pause button and write what the plot will look like in your notebooks. So let us see if you have this answer correct. So if you have let us say a K observed value what you would see is that the plot would be a straight line as I told you it does not depend on concentration of HA. So this would be a straight line. So let us say this is the plot at pH is equal to 2. Now if I do the same reaction at pH is equal to 6 or 7 okay let us say I am doing the same reaction at a pH equal to 7. What will happen to this plot I want you to think about it. So I want you to draw the plot when I do the same reaction but now I am varying the pH I have the pH at 7 what will the plot look like. And it will be a straight line because it does not vary on concentration of HA. But now will the K observed be higher or lower at pH 7. pH 7 means right if you are doing say the reaction in water the concentration of protonated solvent which is H3O plus in pH 7 would be greater or less than pH 2. pH 7 is less acidic right compared to pH 2 if you I mean has a lower concentration of H3O plus right compared to pH 2. pH 2 is more acidic. So what will happen is you will have a lower K observed value but again it will still be a straight line. So this would be at pH 7 alright. Now I want you to think what will the plot of K observed versus B look for a specific base catalysis. So we have already looked at specific acid catalysis here now we are plotting K observed versus B what will this look like. So again let us start with pH 2 and pH 7 now that we have this example on the left you can go ahead and draw it for two pHs pH 2 and pH 7. So what you would see is at pH 2 in this case you will have a lower rate. If you remember the expression in this case the H3O plus concentration was in your denominator and we are looking at a base catalysis reaction. So having an excess concentration of H plus will not help you. So the K observed would be lower at pH 2 again just by the definition specific base catalysis what that tells you is that it would be a straight line it will not vary with the concentration of B and what you would see is it will be higher at a higher pH alright. So you see a complete switch here where when you are doing specific base catalysis the K observed value is higher at a higher pH. The last thing that I want you to think of before we end this class is in the case of specific acid catalysis how do you think the log of K observed will vary with pH alright. So remember now on your X axis you have pH and not concentration of the acid HA. So I want you to think how it will change with the pH. For specific acid catalysis we saw in the previous slide that for lower pH you have a higher K observed and for higher pH you have a lower K observed. So what you would see is as the pH increases this value will come down alright and if you look at the specific base catalysis you would see the exact opposite trend. What you would see is that as the pH increases the K observed value will increase and what you would see is this will have a slope of minus 1 and this will have a slope of 1 alright. So we will stop here and in the next class we will look at the general acid and base catalysis and we look at reactions where you can actually see the specific acid catalysis and specific base catalysis. Thank you and see you in the next class.


I will return Dude these moments are too sweet man and now look where we are He's just in way think that happened to him. That's why don't even know like how close it is to Wait, what isn't the sky? What is that? It's croc buggy has a marine hat.


So do you guys want a fast and easy method in earning levels in this game? Well that's what I bring you today guys. So earning XP in Hogwarts Legacy is a must to level up and today I bring you an incredible method. An insane method to earn roughly 2000 XP in minutes. No other quicker way in this game to earn this XP. It is limited to that as far as I'm aware. There may be a way around this you guys tell me. But as far as I'm aware guys it's roughly 2000 XP and earning super super fast. You don't have to fight any enemies or anything like that. It's just crazy. Now have your attention guys. If you do enjoy the video leaving a like really helps me out if you like what you see. I want to see more Hogwarts Legacy on a daily basis. Make sure you subscribe and turn those notifications on. Okay so to do this guys you need to have completed a quest. One of the main story quests called the Elf, the Nabsack and the Loom. Because you need the Nabsack so you can capture those beasts. Now this is around the 30 to 35th main quest though mission. It may be a little less than that but I've done so many in between. I'm guessing here I've done this when I was about a level 13 or 14. So around that level guys you should have and look out for the Elf, the Nabsack and the Loom. Once you do this you gain the ability to capture those magical beasts. So yes get to that point guys and combat you this and you'll be able to use and abuse this and get that easy XP. Okay so how it works it's quite simple. Make sure you have your Nabsack applied to your spell diamond. Like I said you might as well be right there. And all you need to do guys is come to this blue flame. Let's pull up my map and we're going to go and capture these little magical beasts. Now it's a way of doing this so you can make them respawn and you can farm them over and over. But yes this is where you want to come to. You want to come and get these Puffskeen. Is that say Puffskeen? Puffskeen den because it's about eight here. You can capture them in seconds. You get 30 XP per each one. Again it's limited to I believe 60 you can capture and then you stop earning XP after that. Like I said there may be a way around this I'm not sure. But hey the through flame you want to come to is the forbidden forest one right here as you can see. So come to your world map and come to there. So travel to here and we're just going to mark this and a map right there. Oh look at that dragon. Okay so I'll show you how I come to the conclusion as well. You can only do 60 times. Come to your challenges. Come to the room requirement. You can see here it says rescue beast. Rescue 10. Then you have to rescue another 20. Then you have to rescue another 30. So the 16 total I believe you can get this for. There's 30 XP per one. So 60 times 30 what's that 1800? Roughly 200. You'll probably do things in between as well earning more XP. Okay so now we've marked on the map where we want to go. I'll show you how you do this. How you farm these and how you can make them respawn. So just pull out your broom and just flow over there.  Use your legs. Now it's just quite easy. I'm just gonna quickly run you through this. I mean you when you get this down it's so so quick. So you can see the dens right there. You can see all the little fairballs right there. Simply just drop down here. I use my finger spell here. You don't have to. The disillusionment spell. You don't have to. It doesn't really make much of a difference. So I just pop that. Then just come up to these and capture them. Now I ain't gonna capture all these because I just want to make video efficient and easy but simple. Just drop your bees capture bag on them and you're done. You see I ain't actually earning any XP but I'll show you a clip on screen now of me doing this and earning that XP 30 per one. So I'm capturing all these guys and as you can see I'll speed this up because otherwise yeah I just want to make this video efficient as you do. Okay so as you can see from right here all you need to do guys is pull out your broom. This way you make them respawn by the way. Pull out your broom. Follow it over this way. You see there's like farm there. Simple as this guys. I've tried to figure this out for ages but I got it to work. Just drop the broom here. Go into your finger. Click on the map. Thrust in your right form sticker. Just want to wait. Turn it to night or turn it to day if you're at night already. And then you want to go back into it and change it again. And this somehow it's like a full day cycle and these little critters they respawn. And it really is that simple guys and you can do this. Rinse, repeat this until you've captured all 60 of these beasts and you do this in no time at all guys. I really mean it's so so quick.  As you can see right there they're all back. And it really is that simple guys. So yes. Now another thing as well what you can do is. Hello little beasts. It's another way of making incredible money too. So once you've captured all these you can well your inventory before. You can do what you want with them. You could just release them if you want to. Or you could go to Hogsmeade. There's a shopping Hogsmeade that buys these beasts off you. Which is just perfect all because you're just going to make tons of money too. So the Bruton Peck this is the place you want to go to. So just go to that flute flamie right next to it. We go there and we can sell these beasts and earn a ton of profit people. And we know gold is needed in this game. And this is a video I've already uploaded but for those who didn't see that this is a way to earn tons of money too. So just run over here and I think you get 120 per one. So if you've got like I think you can hold when you first able to use a knapsack. I think you only have 20 inventory slots to sell. But as you progress the game you'll earn way more slots. So yeah guys you can sell all these now. 420 each and get super super rich at the same time as earning tons of XP. But yes guys there we have it and well I hope you enjoyed the video. If you did leave a like who really helps me out. If you like what you see and want to see more Hogwarts legacy be sure to subscribe if you want to join my discord Hogwarts community. Talk about the game share your character share your your secret share your build whatever my discord is linked down below. But guys thanks as always for stopping by and hopefully I will see you on that next one.


Welcome back amigos. Great to see you here. My name is Usheen Lonnie. I'm delighted to have been your host here this morning on Track 2 at the Big Things conference. Now remember we have a digital treasure hunt and you are collecting points just by logging in and just by joining us for our amazing next presentation. Now I promised you at the beginning of the day a power trio of sessions and so here is the grand finale here on Track 2. I'm delighted to be welcoming two gentlemen who are going to talk about implementing a multi-cloud customer data platform or CDP in Google Compute Platform and the Mighty Salesforce. So this is actually a production use case of a multi-cloud CDP which is elegantly walking the line between personalization and anonymization. So prepare to get yourself connected with making science's design approach and you too can deploy an advanced and agile CDP in a cloud agnostic manner. Do remember to get your questions in as the presentation is happening in the chat window. We do our best to ask these to our rock star speakers. Do remember to share the love using the hashtag BigTH21. Okay so it's my pleasure to welcome to this stage Kevin Daly who is the first party data director at Making Science. Hola Kevin, he is joining us via the magic of Zoom and Juan Manuel Pozo who is the senior data ops engineer at Making Science. So Kevin, Manuel, join us on the virtual stage. Thank you. Okay now using the magic of technology we are going to beam straight back. We have teleported Juan Manuel into the studio, into the mothership here at BigThings Conference and we have Kevin joining us remotely. Bienvenidos, welcome Kevin. How are you? Fantastic. Good afternoon. Muy bien. Okay, bienvenidos. Right, so I'm going to step aside. Kevin, we're going to hand over to yourself for the intro and then Juan is going to take us on a deep dive of the text. So Kevin, welcome. Thank you for joining us. The stage is yours. All right, thank you. So as indicated I will start off a bit fluffy. I'll give a bit of background on the drivers positioning and why some of our customers at Making Science are requesting a multi-cloud approach to CDP. Manuel, let's go forward one slide please, since you're driving. There you go. Actually, we've gone a little too far. In any case, not all of our customers are demanding a multi-cloud CDP but year over year, because we've been in this space now for quite some years, we are getting more and more interest and it starts to fit in with the noise, the drivers, the movement about data democratization. I'm an old guy. I go back in time pre-internet, if you can believe that. I'm sure most of you are post-internet. But I remember what it was like to have to look for data, to look for information, having to go to a bookstore, go to the libraries, talk to friends, talk to colleagues, to pull information together. Now with the internet, we've all got it just at an easy reach and that's part of the data democratization process that's starting to occur with businesses. They're saying, why are we just leaving the data sitting with the BI team or the IT team and letting them farm or mine that data. Let's get it out to all the business units. As we know, there's more and more tech-savvy people coming out into the industry. So pushing that data out into the business units does make a lot of sense as a businessman. We're seeing that tools are also getting easier to use. Every year, all of the BI tools are getting easier to use. So your analysts are finding it far, far easier to work with the data. These are the drivers in any business that wants to become data-driven. But we can't forget about an age-old problem and that's about data governance. The data governance is one of those things that still has to be in play. The data governance is all about making sure your metrics are calculated consistently for the business. There's a clear definition of how those metrics are calculated. You've got the controls in place to make sure you've got no holes in your data, your data's current, you've got no duplicates, all of the normal things. So we can't forget about the unglamorous part of data democratization and self-service analytics. These are underlying elements, okay? Forces moving us in this area of a multi-cloud CDP. But before I get there, you may ask yourself, well, what's the real value in the data democratization? Because between Manu and I looking at the same data set, our same data, we can both identify and potentially bring to the business new insights, very different insights over the same data. So it really, it's making the business more efficient, but it's also helping the business make far better discoveries over the same sets of data. Let's go forward, Manu. As we talk about a customer data platform, we talk about first making that data available, getting the data governance there, making my tools available, making sure I've got all my metrics calculated, that is accurate. But making science, it's not about having the data and the insights, it's the next step that really gets interesting and brings value to the business, and that's activation, okay, or activating the data. So taking action with those insights. And this is where many of our customers, it doesn't matter whether we're talking about finance, or we're talking about telco, healthcare, insurance, there's some types of actions that we may be taking with that data that sits over top of sensitive accounts or sensitive information. And that data is going to be typically sitting within, what we've called over the years, a walled garden, okay? In this customer that we're going to look at today, it's an environment where we've got a Salesforce marketing cloud, a Salesforce service cloud, and a customer data cloud, which is a correlation of information from all the sources, websites, back office, back office CRM, back office marketing, bringing it all together into that customer data cloud, but it's all still sitting within the walled garden, because in this customer there's a lot of sensitive information. Sitting just outside of that walled garden in our CDP as a concept and architecture, we've got the analytics area. And this is where we really turn the data scientists loose, the business analysts loose to do their magic over the top of the data. But when they do their magic, they make those discoveries and they want to pitch back into the customer, maybe a marketing campaign, a cross-selling idea, upselling idea, maybe an adjustment on an account. That information is going to be communicated back into that walled garden. And today, our discussion with Manu, we're going to take a look at how we move data from the walled garden into that marketing analytics part of the CDP, and then how we take the insights that might come out of that, an offline scenario or continuous analytics scenario and pushing it back in to the walled garden. It's an interesting, it's simple enough for you to understand. Technically it's a bit challenging. Most customers are focused on just getting a customer data platform in place to enable the marketing teams and the analytics. But here we've found a nice balance to keep the IT community happy and the marketing community happy within the same customer.  If we take a look at, what are some of the characteristics or the differences between those two clouds? This slide for me sums it up pretty well. The customer data cloud is, it's an IT space. It's typically managed, run by the IT departments. I'm an IT guy by education and background and experience. IT personnel typically are very focused on security, stability, reliability, controls. The customer data platform, the Salesforce platforms, your online transaction processing systems, your accounting systems all fall into that domain of that customer data cloud. On the other hand, the marketing analytics cloud, a piece of your CDP, that's all about agility, experimentation, speed first, fast fail. I'll say anything goes when you're trying to make those discoveries and insights. And again, what we've done with our CDP approach, multi-cloud, is making sure that we are serving the governance requirements, the legal requirements in maintaining the private attributes, very confidential, very controlled, a limited set of accesses, very known rules in terms of how the data can be utilized. And on the other side, we're making that anonymized data available to the marketing teams and analysts to work very fast to try to look at new flows, new discoveries, new insights, and then pushing that information back into the customer cloud for the route of activation. And on that, I'd like to hand it over. We're going to take you through, I've got one more slide, Manu, go in this slide, starts to present, okay, peeling the onion a bit deeper. We're not going to hit every one of these boxes today. Some of this stuff is very, very traditional in terms of, I'll call it ETL, so you've got your transmission, your events processing. Where we're going to focus today is in the middle area of how we're going to be moving the data between the two clouds. So again, we're not going to try to do it too deep on the far left or the far right, because we're sort of limited on time. We're going to look at how we're going to be moving that data between the two clouds, both taking the data in a transparent form into the customer data cloud, anonymizing certain attributes of that data, pushing that anonymized data down into the marketing analytics cloud, storing it, allowing the insights and analysis to occur, and then showing how that anonymized data comes back up into the customer cloud for de-anonymization and activation over the given channels. So on that, I'd like to now turn over the floor to Manu to take you on a bit of a deep dive into some of these components and how we make this happen. In a real client environment, it's following this philosophy. So before starting the presentation, I want you to think about a batch loading data, receiving the files in CSV, and processing a lot of millions of data in batch. So first of all, we need to focus in one part of the flow. In the customer cloud, you can see there the API mapper, which is called the API mapper, but it's really an app engine which has the mappers to be able to recognize the file origin and how we have to process it, okay? So we are going to go deep in it and we are going to see an example. You can see there how are we mapping the CSV file. We are mapping the fields needed, so we also can check if the CSV file is correct or not before starting the processing. Also, for each file, we have a property that tells us if we have to anonymize it or not. For example, in this case, the only field that has to be anonymized is the NIF, which is the client identification. With this mapper, we can generate a new file with the sensitive information of the client anonymized, and we can move it to the market cloud. You can see that there is a lot of other parameters in the JSON file that we get from the app engine, but those parameters are used in the marketing cloud just to transform, for example, in this case, the dates to have them in a correct format for us and for the data science team. The system that receives the information is the Kubernetes, where we deploy our code, we call the API mapper to recognize the file and to know which parameters do we have to anonymize, and we anonymize it with a hash. It's a little more complicated because hash values cannot be the anonymized, but we can store the anonymized value and the real value to check it before, to check it after. This is a common method to be implemented. It's public, it's a public library, so it's not very complicated, and the next thing is to store the results to be checked after. We use Firebase because we want to have a real fast answer when we want to recover the values. You can see an example in the slide where we store the hash set value as a document to be able to use the fast property of the Firebase. Okay, once the file is anonymized, we create a new one in the Google Storage and a Cloud Function recognizes this save and informs our marketing platform to ingest the file. This is also a very common Cloud Function that is triggered by a change in the Google Store, so it's very simple. We just give the marketing platform the information of the file name and the storage, the bucket, where it has been saved. Now, in the marketing Cloud, we just have to do three tasks. One is to save in Google Storage the original file just for security matters. Another one is to load the information in BigQuery in row without any modification, just saving the timestamp and so on. The third way is to save the information in BigQuery, applying some modification like the AppyMapper modification which we saw before that we changed the type of the dates. We transformed strings to numbers, strings to dates and so on. On the other side, once we already have the data loaded, we have a team of data science that use Dataflow and Cloud Functions to compile information and to generate a response. For example, thinking in a common use that I'm sure you already live it, you buy something in a shop and then an email reach you with offering you another product. In the previous slide, we have seen how we have loaded the information of your put chase. The marketing Cloud is going to take your identification, it's going to search your put chases and it's going to generate a response to the customer Cloud to send an email offering you related products of your previous put chase. We don't know your information, your personal information, so it's the customer Cloud which is going to change that anonymized information to the real information. It is going to use Firebase as I said before and it's a very simple de-anonymization. This is another architecture that we are working on right now. It's going to be deployed, we hope, at the first quarter of the next year. It's basically the end of the architecture is the same, but we are trying to focus on self-oriented events, to receive events instead of batch events and the different models are independent in Google. They are self-controlled, they are serverless and it's more comfortable for us. For example, Kubernetes is very potent, but we are wanting to offer an architecture that is serverless. This is a more serverless approach. As I said, a more event-focused approach and that's it. If you have any questions of the architecture, I'll be pleased to answer you. That was very interesting. Thank you so much for taking us to the brilliant Juan Manuel and thank you so much Kevin for beaming in. I would just take issue with one of your remarks being the old guy. I think you're spectacularly young. I think it's all relative. I remember being introduced to a group of young folks as this is Usheen and he's from the days before the internet and I did indeed feel a little bit prehistoric, but what the hell, we've got to own these things. Thank you, that was absolutely brilliant. Folks watching at home, don't forget, you can get your questions in on the chat function and they will be beamed to our magical iPad here, but I just have some questions myself. We've seen some innovative data architecture there. This is an interesting, really interesting new platform, very innovative and it's about building new connections between data. You spoke about how this is going to be useful for folks in marketing, for folks in data analytics, for folks in IT. I'm wondering, this question to both of you, are there any use cases or uses of the platform or technology that companies are missing out on? Can I do some wonderful things that maybe many people don't know about or more companies should be using because it's a competitive superpower? Any insider tips for the folks watching at home? I'll start, Manon, you can come in wherever you want. In our space, which is very focused in digital marketing, there's been a bit of a paradigm shift and again, that customer data cloud, CRM systems, it's the area that's known as first party data and in marketing teams until recently, didn't really have access to first party data because it was confidential, it's very private. Again, it's following the IT rules to business. So what we're doing is showing some very large customers across sectors, the ability to move that data, take advantage of that data, they're the custodian of that data. They don't own it, the consumer owns their data. The bank or the insurance company is just the custodian, but allowing them to leverage that data to serve their customers better. In some cases, in this example, we were allowing better targeting of medical doctors based on certain conversations that were happening, applying natural language processing behind the scenes. The data scientists that put up the models and all that intelligence and recommendations in terms of the best doctor, they didn't know who, if it was Kevin or Manu's conversation that was occurring, it was all anonymized, but they saw the text, the conversation and they could make a recommendation as opposed to using a generalist, they could get to the specific doctor needed. That was a real big benefit that they were able to take advantage of in that first version of the system as of a year ago. Absolutely, I love the AI, machine learning, NLP under the hood to help businesses really super scale. In this world of interconnected ecosystems, as I was saying a bit earlier, you do need those connections and you do need that help for machine learning and AI to really bring your business forward. Similar question now for you both. Are there any new business models that you think could evolve from this technology? You're joining the dots, you're bringing in big data and machine learning and natural language processing. Do you think this could give birth to new businesses and are there any sectors or areas that you see could be a weak point as to... This one excites me because we, like I said, I'm an IT guy, I've got a lot of responsibility for hiring and all of us.  If you're an IT guy, you want new projects, new opportunities and there was a time in which, again, the data in the walled garden, only certain people could have access to that data. Now, if we're putting it into an area that's governed, it's anonymized. I've now, as a businessman, I can now reach out to experts out in the field. I can open up my door to new IT partners to leverage the data, come back to me with insights. I've now just taken my IT team and I've made it virtual. I can reach out to anywhere. I'm sitting here in the north of Spain. You could be in the south of Spain. You could be in California. You really can take advantage of making your data available to the best resources wherever they're located in the world. Amazing. Absolutely. I think this is going to excite IT staff, excite folks who like building new stuff. This can be an amazing tool for both recruitment and also retention as well. Does anybody really want to work so much with silo data and where stuff is complicated and difficult to connect? Having this kind of access to open data and these connections and plugging in stuff like machine learning, NLP and AI can really just make things more fun for brilliant scientists like yourself. I like what you said in the intro there. You are turning the data scientists loose to really kind of build the future there. Folks, I'm afraid we have wrapped up our time. We've just got a little bit of time left until our amazing keynote presentation over on the main stage. I just wanted to say thank you so much to Kevin and Juan Manuel from Making Science for bringing some magic here to Big Things Conference 2021. Thank you. Muchísimas gracias. Thank you for joining us remotely, Kevin. Thank you very much. Muy bien. Gracias. Folks watching at home, don't forget to share the love using the hashtag BigTH21. If you learned something new about data science and about data connectivity, I certainly did using that last presentation. Please share your thoughts. Please feel free to tag me and Big Things Conference and use the hashtag BigTH21. And don't forget, there's still loads of time for you to win that brand new iPhone 13. Just take part in the gamification section of our website, even while you're watching the speakers. In fact, watching us right now, you're collecting points. How cool is that? Make sure to network, make sure to apply for some job opportunities and make sure just to get involved. Everything you do pretty much is going to give you extra big points to bring you closer to vouchers, books, and that iPhone 13. Okay, so that's it for Track 2 this morning. Make sure to share your thoughts on what you thought was a great session, like the one we just watched, like all of them to be honest, this morning here on Track 2. Share your feedback using the evaluation tool. Tell us what you liked, tell us what you want more of, and we will make sure that next year's event is even more awesome. It really does help us to improve, and we appreciate your time in sharing the feedback with us. Okay, and if you do win the iPhone 13, if you win any of the prizes, make sure to take a selfie and share it using the hashtag BigTH21. We're going to move over to the main track shortly. We're kicking off at 1320, 20 minutes past one here in Madrid, and we're going to welcome a real Rockstar speaker. He is the global CIO of Zoom, one of the companies that really has helped us all get through the pandemic and through the lockdowns. He's got some amazing, amazing things to share with you, and he's going to put some big ideas in your head and show you some big things for the tech awakening and for the future. So, my name is Usheen Lune. It's been an honor to be here this morning and to connect with you. Feel free to connect with me on any of the socials, and I'll be checking the hashtag BigTH2021. Tech is Awakening, and the future looks amazing, and I will see you there.


Hi, so we are about to race in Portland, but before Hannah stopped in the Hood River and I was lucky that the geotone equipment was here so we could get some riding with... Colin. Oh, hey, hey, Colin. She's a pro rider and she was very good on water. Good morning from Portland and today is an important day as we are the 11th of September 2021. So that marks the 20 years of the attack, 9-11 attack and we're gonna take a moment of silence before starting the day with everyone and then we've got to pre-practice one session, qualifying, warm-up and then on Sunday the race. It's cloudy today which is gonna make things different. Yesterday the quality didn't quite go to plan. We had a bit of an issue and then traffic and then I did block to spot my clockling. Being myself block was another guy so I ended up in penalty so starting 21st today and let's see what we can do from there. See the paddock here, the sky is grey and let's see what we can do. We're down from Portland to Laguna Seca. It's about 16 to 17 hours drive so I've stopped in... actually just the border between Oregon and California So I'm in California, just came from Oregon 6 hours drive there, it's been fun and we've got my good friend Olivier who is also my race engineer which is parked here. Right next to me he actually just came to rescue me on my bike because I had two punctures but only one spare kit so he wasn't far and he came to pick me up on my bike and now we're going to spend the evening together and tomorrow Napa Valley. 6 hours of driving today, we are stopping yeah a little bit of nowhere but we're going to get a coffee with Olivier he's both down there and then on to Napa Valley so yeah, 6 hours of driving but now we are stopping for a bit of lunch. So here we are in Napa Valley at Jimmy Vassar's place, tasting wine and that's pretty amazing. It's a long beach, look at this. Now we're just going to cross that street and be on the beach, which is pretty good for a race track I just wanted to show you one thing, here it is Look at that, look how tight it is It's good fun but it's tight So Todd, let's analyse Todd's positioning No pressure Todd No pressure What are you saying boys? Mike Horn, what are you saying? It's open, it's an amazing time Yes, check it out We are organising a quick BBQ with everyone which is cool to celebrate the first really nice season in the car