thank you all of you for being here today it's such an honor to be here and the idea today is to go through a trip all together we're going to travel through the past present and mainly the future of uh data um it's true that data has always made part of history and although that it said today that data is the new oil data was used from um very very far away in the past in the ancient Egypt for example we didn't talk about data but we talked about statistics and um in the year 2600
before Christ when they were building pyramids they were using statistics so yeah it seems to be something really brand new but it's not that it and then also many governments use data for the last 150 years and in Spain for example we have the census campaign first one it was in the year um 1856 and from the year 1900 we've been having census every 10 years without any Interruption and we're using this data we're using this statistics for many purposes but for example to decide when and where to build schools or hospitals based on the
age and also on the growth of a population in its cities these censuses are also used for other purposes that we all know for example to decide taxation okay based on the number of inhabitants and also the wealth of each City so this is about the past and if we move on into the present we'll see that nowadays we talk about a lot of Concepts connected to data some Concepts difficult to Define and here today the idea is to make something light for you but for example you've all heard about data warehouses those electronic systems
where we store information in a secure and reliable way for example also in business you set the business and we talk about business intelligence is the way we use data to take good decisions in a business and it helps us to make our companies grow and then we have uh Data Mining and big data analytics where we look for patterns we look for correlation between different events and different variables in order to take also some decisions or try to conclude something then we have Predictive Analytics that tries to answer to this question about what will
likely happen so we gather all this data and we try to predict the future for example we have the World Cup now and we can gather all the information and try to decide who which company is going to win this competition then we also if you go inside ourselves in human beings we also have cognitive analytics that tries to predict somehow human behavior and how you as students and our citizens will behave in the future based on the patterns of their Heritage their parents and also their behaviors nowadays and then we have something that goes
even far away which is the augmented analytics that uses the natural language processing and also some machine learning in order to extract intelligence and in a way that is quicker and and simply in order to go the extra mile so these are seven Concepts that we're using right now and that's some years ago we've never heard about it so nowadays the present uses of data data is everywhere okay and it's not just about um business because if you see Finance for example we have portfolio data and what does this mean well is the use of
data of information in order to decide where and when to invest sometimes it goes well sometimes it doesn't because data somehow even if it's used to predict future events it's not that easy to see what's going to happen in the future and I'll explain you why later on then we have also people I was HR manager before and we start using PayPal analytics HR analytics what's this for mainly it is to try to improve the talent within our companies try to get the most out of our labor force and it's something really brand new because
HR departments did not have access to data but now with the new softwares being used by companies it is possible and it's something good it's something positive and then obviously we have sales analyzing the customer journey of clients and deciding in its touch points where to use those variable data those information that you got from the patterns of your clients and this is when after all you're going to buy more this Black Friday because all companies gather all information from your patents and they will attack you with those advertisements that you will see with those
products that you really need but there are other uses of data nowadays we can see medicine for example to see some patterns of some hereditary diseases and also in the pharmaceutical sector to try to predict which is the best drug to use for each disease and how will a patient react to those medicines then we have sports again as I told the World Cup that is going on but you know all um on athletes nowadays they have something here that gathers all those information of the kilometers they run whether they went left or right and
when we're going to the World Cup final if it goes to penalty kickoff each goalkeeper knows if that player is going to shoot right left up and down because all these teams gather all this information it's easy even to predict that a country will win a competition or not but you never know because uncertainty is always there um and for example other uses of data we have mobility and it's something good to create better cities because with all those travels that we make um walking because we have mobile phones that are connected to GPS or
public transportations then Town Halls they may create this um heat maps and they know exactly where people are so they can actually decide if buses are going one way or the other in order to live better within the city and also in the logistics if you have to deliver a lot of packages intelligence business intelligence and data analytics will create you the best route in order to do it in a more efficient way okay we talked about the past we went through the present but we're here to talk about the future this tedx it's about
the future of business and this talk is about the future of data so what will the future of data be like in the future this is a really hard question to answer and I would say that the future of data will be determined by the five V's of data first one volume it's the amount of data that we're using more and more and more data second V the value and the value is related to the more operations that are driven through data we've seen before that more and more operations that didn't use data before now
are using data then we go to the variety the different range of things that we can apply to when using data then velocity the speed I mean I've been talking here for five minutes and in this five minutes I'm pretty much sure that a huge amount of data was created and if we want if we access our mobile phones we will have access to that data this didn't happen 10 years ago this and this didn't happen 20 years ago and the the the the the fastest it goes the more volume of data we have been
creating and then something also really important nowadays that we talk about a lot of fake news is veracity the fifth V of data it's knowing about what it's good what it's bad what it's true what is false and in a world form of data it's not that DC easy to distinguish whether something is good or bad so this is kind of the biggest challenges of data for the future and it is kind of paradoxical because we use data to predict the future but on the other hand the future of data is kind of unpredictable and
why is this well Specialists say that we are living in a Banning world you know that bani stands for Britain anxious non-linear and incomprehensible and it's kind of an improvement of the past vuca kind of view of the world which was the the the the the volatile uncertain complex and ambiguous so we made an upgrade and it's even more difficult to predict things and my question is what are the challenges what are the barriers what are the limits of data and I'm afraid that the answer it says it's you people and why do I think
that well I'll give you my personal view about this and here I'll leave you with some statements first of all data it's only valuable if you are the one who has access to it if there's another company or another person that has access to that data then this won't mean an advantage so when you are the first one going to the market you can create barriers on that market which will make you leader of that market but then in the future with the speed and the democratizing of access to data you will no longer be
the leader anymore if you don't continue to do things better you don't have more competitors and there will be no barriers then third the time the time between you Gathering that information and the time you take a decision of what doing with that information will make the difference because First Data will be accessed by others and second if you take too much time to decide that data won't be useful that data won't be reliable anymore because of the speed because of the Velocity I talked before and fourth companies are starting and this is quite risky
they are starting to be not data driven but data obsessed you know that companies sometimes ago they put Client First clients always right then they decide to be results oriented and now they say that they are directed data driven the thing here is that with the amount the huge amount of data they have they're not being data driven they're being data obsessed they don't know what to do with data and I think that it will be easier and best if you put people in the center because if you put people in the center people are
the ones that are going to give a good service to the client people are the ones that knowing the results will Foster and try to grow and reach those numbers and people are the only ones that can actually decide what to do with data so that's why it's so important to put people in the center and I think that in the future we will have two kind of people two types of people and also two types of companies the ones that really see in data the solution and the ones that seeing data a problem because
they don't know what to do with that and same thing applies to governments having a lot of information maybe dangerous if this information is gathered by a government that has some ideas that are not very Democratic because they can decide what to do with those informations and we have an example for example of data in the past Mr Schindler at the list of 1200 Jews and they decided what to do save them from the Nazi but he could have decided something completely different so it's not about having or not information it's what you do with
the information and that decision is made by a person so we must be prepared and you are quite in the barrier of being um a data native generation because in the future our children they will know exactly what to do with data because they will be prepared to process all that information because we are not because we are in this life with a lot of infinite from information with lots of data but we were not prepared to do so that's why we have to go faster and same thing with big corporations they have when you
go your mobile phone you see those ads you tend to buy and you say oh this is fantastic because I was just looking for that but then you start thinking about it and you start to be apprehensive and you just have to be afraid and you start not accepting cookies reject our cookies because then obviously you will realize that your mobile mobile phone knows more about you than your best friend your boyfriend your girlfriend your mother even yourself and this is quite frightening and again what do you think people reaction will be to this amount
of data to this new reality they won't close themselves and this is quite dangerous because we will work in silos in the companies because we won't have the ability and interest of showing and sharing and also um it will be dangerous because if data goes in the ends of non-democratic governments they will think about what to do with that they will try to influence you and we can go even behind with a cognitive cognitive analysis and we can see these governments installing chips in your head and making you decide what to do or if we
are in kind of a reality where everything is recorded and with uh the interaction we may have with cameras they will see our patterns and we'll they will know exactly how we film and how to motivate Us and how to led us to what they want to decide so main conclusion of this is that the only agent capable of changing the future it's one the individual because this will be the one if well prepared that can make with data something good and not something dangerous and to finish last conclusion is that no matter how much
technology science and data evolve the human being will definitely always always be in control thank you very much [Applause]
