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Germany's World Cup tactics: shaped by data. Player performance is analysed using eight cameras that surround the pitch. The pitch itself is transformed into a grid, and each player is assigned a unique identifier, allowing their movements to be tracked digitally. This data can then be used to measure key performance indicators, such as the number of touches, average possession time, distance travelled, movement speeds and directional changes. For the German national team, one of their key targets ahead of the World Cup was to improve their passing speed. With the help of SAP's Match Insights technology, the team was able to reduce average possession time from 3.4 seconds in 2010 down to 1.1 second in 2014. "SAP’s involvement has transformed the football experience for coaches, players, fans, and the media," said Oliver Bierhoff, manager of the German national football team.

"Imagine this: In just 10 minutes, 10 players with three balls can produce over seven million data points. Inside Telecommunications - Issue 14 - Service innovation. Unlocking new opportunities in big data Global spending on big data technologies and services is expected to grow 30% in 2014, surpassing US$14 billion as demand for big data analytics skills outstrips supply1. Operators have many advantages compared to other industries when it comes to repurposing data to improve decision making and create new demand scenarios. A wealth of product, customer and asset data lies at their disposal, while their legacy retail and distribution capabilities also provide a range of customer touch points. This promising position is borne out in average big data spending levels among operators, which outperform those of other sectors.

A number of factors are setting the stage for greater proliferation of analytics tools. Data storage costs are falling, and the use of open-source tools, such as Hadoop, is compounding a healthier cost profile for analytics solutions. Sample big data use cases for operators Source: EY analysis. Ready for takeoff? Overcoming the challenges of big data. Big data is an innovation that businesses can use to drive competitive advantage. But the value of big data lies in the insights that your business can draw from it, rather than in the information itself.

Big data refers to the huge and increasing volume of the data available, and the ways it can be processed. Data comes in many forms, structured or unstructured, and it may be generated by organizations themselves or obtained from third parties. Analytics is the means for extracting value from this data by generating useful insights. Without analytics, businesses have no way of using their big data to establish competitive advantage. Issues and risks Your business needs to overcome practical problems like the shortage of people with the technical skills to generate insights, and strategic challenges such as implementing big data adoption across the organization. There are also serious legal and regulatory risks around issues as data privacy that can result in breach of trust. Next. Helps AIB Promote its Digital Strategy and Capabilities. AIB and Accenture worked together to define the initial concept, devise the customer proposition and target model, and collaborate with other vendors to design and implement the solution.

An Accenture team of local and global banking, digital technology, digital marketing and mobility specialists led the following project components: Overall program management, including delivery objectives, scope, roles, responsibilities and governance.Operating model development for the store, including staffing (recruitment and training) and transition of the project to a live and stable business. Marketing and social media specialists from Accenture helped AIB launch The Lab (see below) with a high-profile grand opening media event. The physical retail store, branded as The Lab (Learn about Banking), incorporates four distinctive store zones to help AIB deliver the target customer experience:

Los sitios más destacados para la formación en Big Data en España y Online | Ideas de un Project Manager – José Julio López. Los sitios más destacados para la formación en Big Data en España y Online Fundación General Universidad de ValladolidHe recopilado los principales sitios de formación sobre temas Big Data, centrándome en cursos presenciales en España o disponibles online, para todos los bolsillos y gustos. Es un tema sobre el que me consultan bastante, e iré añadiendo más según tenga conocimiento de otros nuevos o con vuestros comentarios. Si lo encuentras interesante, por favor recomiéndalo y compártelo. No dudes en contactar conmigo a través de mi perfil en LinkedIn.

Gracias a todos de antemano. He agrupado los recursos por tipos, aunque no siguen un orden de relevancia. BigData4Success: Antes de nada agradecer a Jorge Ubero Ambel y su sitio llamado Soydata con varios cursos gratuitos o económicos, de donde saqué información para elaborar la primera lista. Programas y Másters: Cursos Monográficos: Cursos Masivos Abiertos Online (MOOC): Si te ha gustado, recuerda compartirlo. Me gusta: Me gusta Cargando... BIDOOP | Casos de Estudio. Mining the CFPB Complaint Database to Improve Your Customer Experience. Omni-Channel Personalization in the Banking Industry. Data-driven personalization is the key to big gains in customer satisfaction, customer acquisition, and account growth.

But the complexities involved in implementing a cross-channel personalization platform can be overwhelming. Here’s a break down of the pieces involved with crafting a personalized omni-channel and cross-channel experience. By Mark Ryan, Chief Analytics Officer at Extractable It’s amazing how many parties benefit from personalization. Pioneers in digital personalization such as Amazon, CapitalOne, and Facebook have demonstrated that customers love it, proven by superior results and loyalty. In our experience with developing public websites, email campaigns, online banking interfaces, mobile applications and social campaigns, we have found that personalized messaging almost always shows double-digit (and often triple-digit) improvements in engagement and correlating improvements in conversion (i.e., personal loan applications). 1. 2. 3.

Data Streams & Platforms. The Financial Brand: Marketing Insights for Banks & Credit Unions - Big Data: Big Opportunity In Banking… Or Big B.S.? Big Data. Everyone in retail banking is talking about it, but no one really seems sure what it is. At the very least, confusion and controversy surrounds how to utilize big data in practical applications, and the magnitude of opportunity is represents. Will big data transform the future of financial marketing? Or will banks and credit unions get crushed by a crippling tidal wave of information?

By Jim Marous, SVP/Corporate Development at New Control For years, financial institutions have leveraged internal insight they have on their customers to manage risk and fraud, as well as to improve product development, and (of course) marketing and customer communications. The question is: Is now the time to embark upon a Big Data strategy? What is Big Data? “There were 5 exabytes of information created by the entire world between the dawn of civilization and 2003. Much of the confusion around big data stems from a misunderstanding about the definition itself. More Data = Better Decisions? The Financial Brand: Marketing Insights for Banks & Credit Unions - Marketing, Numbers, Math and Science. Marketing has changed a lot over the years. What used to be a field of dreams has become a battlefield in which massive armories of technology and data are brought to bear in a neverending quest for domination. In other words it has become, supposedly, a serious enterprise.

However, confusion reigns. One of the main sources of disarray is a misunderstanding of marketing’s relation to numbers, math and science. Marketing, of course, is none of these, but a business function, and to be practiced seriously, it needs to be treated as one. Marketing as Numbers Good hard-nosed business people are fond of saying, “show me the numbers!” We have no shortage of metrics, such as awareness, sales and advocacy, but each have their drawbacks. Another problem is that numbers are essentially backward looking. Simply looking at numbers tells you very little. Marketing as Math Often confused, there’s a fundamental difference between numbers and math. Math, in other words, requires imagination. . - Greg. What Is Big Data? (and what do we do with it?) Big data is like Moneyball for geeks. The term itself is so innately exciting that it made the leap from neologism to buzzword in a heartbeat.

Mostly, that’s a good thing, because it has undoubtedly increased enthusiasm and investment in a crucial area. Unfortunately, all the hype also has a downside, because we are now in the midst of a big data bubble where everything and anything seems to be touted as having some kind of big data tie-in, which makes it hard to know what we’re talking really about. In their book, Big Data , authors Viktor Mayer-Schönberger and Ken Cukier define it as “things that one can do at a large scale that can’t be done at a small one” and that, I think, gets to the heart of the matter.

The Problem With Facts In order to make a clear comparison with other players, however, you would also need to be very careful to create controlled conditions, including standards for the ball, the height of the net, lighting conditions in the gym and so on. Deep Learning In Blink. It’s The Math, Stupid. Are you data driven? Do you live by the numbers?

If you are, then you’re probably wasting an enormous amount of time and energy. Even worse, you’re probably getting a lot wrong. In the neverending quest for substantiation and certainty in corporate life, we have used numbers as a panacea. In truth, what we really need is fewer numbers and a whole lot more math. Imagine that you’re standing in a room with a group of people. Average is a word that gets thrown around a lot, but most people don’t know what it really means. A mean can easily be thrown off by extreme values if the data is skewed . A few unusual values can ruin the whole concept of an average as a central tendency by moving the mean far away from the most common value (i.e. the mode ). There is a special case in which the mean, median and mode are all equal and it is known as a “normal” or Gaussian distribution (after Carl Friedrich Gauss , one of the first people to use it effectively), but is often called a “bell curve.”.

Bayesian Strategy. Hannibal Smith, the fearless leader of the A-team, always loved it when a plan came together and on that campy ’80′s TV show, they always seemed to, no matter how intricate and contrived. It seems quaint now. In the real world, things rarely happen as we imagine they will. As Mike Tyson, another icon from the ’80′s, liked to say, everybody’s got a plan until they get hit and, like it or not, we all get hit, usually sooner rather than later. When that happens, as it inevitably always does, even our best laid plans go awry.

In truth, planning has never been about strategy, but control and control has always been an illusion. The Rise and Fall of Strategic Planning When Alfred Sloan conceived the modern corporation at General Motors, he based it on hierarchical military organizations. Orders flowed downwards and your rank determined your responsibility. By the 1980’s, the seams started to show. Today, planning has become even less tenable. Why Our Numbers Are Always Wrong - Greg. Co-Creation and the New Web Of Things. “Build a better mousetrap and the world will beat a path to your door.” That notion inspired generations of tinkerers, innovators and entrepreneurs. Of course, then some whip-smart MBA got hold of it and it became “build a proprietary supply chain and a captive distribution channel and you can earn superior returns on your cost of capital.” Scale, rather than inspiration, became the path to competitive advantage.

As digital technology pervades the physical world, the principles of scale are changing in a profound way. I wrote about the difference between the Web and the Internet a while back, but here’s the short version: The Internet is essentially hardware – a patchwork of fiber, frequencies and protocols that link together the world’s computers. In other words, the Internet delivers connectivity and the Web provides universality. The short history of digital technology has been an ongoing interplay between these two architectures.

That’s the essence of the Web of Things . - Greg. The Data Divide. One of the great concerns of social scientists in the 21st century has been the digital divide, a stratification of society into those who have new economy skills and those who do not. The mobile internet and cheap handsets have helped make enormous progress toward closing the digital divide, but have opened up a new rift, this time between firms who are able to use data to create value and those who are getting left behind. To help bridge the gap, UC Berkeley’s School of Information has begun a Data Science Masters Program that will train a new breed of professionals to manage big data. As the Web of Things becomes ever more pervasive, big data can no longer be considered something only tech companies do, but must be embraced by executives of all stripes.

A New Breed Of Businesses We live in a disruptive age, in which the average lifespan of a Fortune 500 company is plummeting while new businesses seemingly spring out of nowhere and become multibillion dollar businesses almost overnight. Why Big Data Matters.