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Big Data, Big Innovation
A practical guide to leveraging your data to spur innovation and growth Your business generates reams of data, but what do you do with it? Reporting is only the beginning. Your data holds the key to innovation and growth - you just need the proper analytics. In Big Data, Big Innovation: Enabling Competitive Differentiation Through Business Analytics, author Evan Stubbs explores the potential gold hiding in your un-mined data. As Chief Analytics Officer for SAS Australia/New Zealand, Stubbs brings an industry insider's perspective to guide you through pattern recognition, analysis, and implementation. Big Data, Big Innovation: Enabling Competitive Differentiation Through Business Analytics details a groundbreaking approach to ensuring your company's upward trajectory. Use this guide to leverage your customer information, financial reports, performance metrics, and more to build a rock-solid foundation for future growth. Build an effective analytics team, and empower them with the right tools Learn how big data drives both evolutionary and revolutionary innovation, and who should be responsible Identify data collection and analysis opportunities and implement action plans Design the platform that suits your company's current and future needs Quantify performance with statistics, programming, and research for a more complete picture of operations Effective management means combining data, people, and analytics to create a synergistic force for innovation and growth. If you want your company to move forward with confidence, Big Data, Big Innovation: Enabling Competitive Differentiation Through Business Analytics can show you how to use what you already have and acquire what you need to succeed.

Big Data - Big Business
The term "Big Data" describes the exponential growth and accessibility of data; both structured and unstructured. Datasets are usually complex, and require sophisticated tools and methods of data analysis in order to make useful insights for improved decision making. This book describes the new technology for organizations to access more data than ever before. We have unfolded the hidden correlations and patterns of data to help companies employ more useful ways of accessing accurate information that can transform their business operations. The Big Data tools we talk about in this book include HADOOP, HANA, and MATLAB, the latter one as an example of a meta-tool used also in machine learning, statistics and neural network design. This detailed information about Big Data tools, methods, and applications will equip readers (business people & organization managers) with advanced knowledge about new technology in business.

Big Data, Big Analytics
Unique prospective on the big data analytics phenomenon for both business and IT professionals The availability of Big Data, low-cost commodity hardware and new information management and analytics software has produced a unique moment in the history of business. The convergence of these trends means that we have the capabilities required to analyze astonishing data sets quickly and cost-effectively for the first time in history. These capabilities are neither theoretical nor trivial. They represent a genuine leap forward and a clear opportunity to realize enormous gains in terms of efficiency, productivity, revenue and profitability. The Age of Big Data is here, and these are truly revolutionary times. This timely book looks at cutting-edge companies supporting an exciting new generation of business analytics. Learn more about the trends in big data and how they are impacting the business world (Risk, Marketing, Healthcare, Financial Services, etc.) Explains this new technology and how companies can use them effectively to gather the data that they need and glean critical insights Explores relevant topics such as data privacy, data visualization, unstructured data, crowd sourcing data scientists, cloud computing for big data, and much more.

Reporting and Big Data. Big Data as one megatrend of industry 4.0 and the impacts on controlling
Seminar paper from the year 2015 in the subject Business economics - Controlling, FOM Hochschule für Oekonomie und Management gemeinnützige GmbH, Hochschulstudienzentrum Freiburg (business administration), course: International Investment and Controlling, language: English, abstract: The global data volume is expected to increase fiftyfold over the next ten years (2012-2022). Reasons for extensive growth of data volume within the era of industry 4.0 are the increased use of sensor technology in production and logistics as well as the extensive distribution and the use of mobile Internet. (ICA 2014, p. 3) But the explosion of data is not new. It continues a trend that started in the 1970s. Changes are the velocity of growth, the diversity of data, and the imperative to make better use of information in business. To harvest and harness every byte of relevant data and use it to make the best decisions is the hopeful vision of organizations in terms of big data. (McKinsey 2013, p. 15) On the one hand, opportunities of big data can be identified in all industries over the entire value chain. On the other hand, many companies are sceptical of big data because of high investment costs, the lack of skilled staff and know-how, and privacy risks. That causes delays in big data s implementation in companies. The careful analysis of the application, and the identification of realizable excess values of big data is one of the controller's tasks. Completely new opportunities and challenges for the controller arise due to the massive growth of data. Though in future the positions of business analysts and data scientists overlap with the controllers' skills and fields of activity. (ICA 2014, p. 3) This assignment gives an overview of big data itself and illustrates the potential in controlling and for the controller. Additionally challenges, threats and risks are determined.

Using R to Unlock the Value of Big Data: Big Data Analytics with Oracle R Enterprise and Oracle R Connector for Hadoop
The Oracle Press Guide to Big Data Analytics using R Cowritten by members of the Big Data team at Oracle, this Oracle Press book focuses on analyzing data with R while making it scalable using Oracle's R technologies. Using R to Unlock the Value of Big Data provides an introduction to open source R and describes issues with traditional R and database interaction. The book then offers in-depth coverage of Oracle's strategic R offerings: Oracle R Enterprise, Oracle R Distribution, ROracle, and Oracle R Connector for Hadoop. You can practice your new skills using the end-of-chapter exercises.

Using R to Unlock the Value of Big Data: Big Data Analytics with Oracle R Enterprise and Oracle R Connector for Hadoop
The Oracle Press Guide to Big Data Analytics using R Cowritten by members of the Big Data team at Oracle, this Oracle Press book focuses on analyzing data with R while making it scalable using Oracle's R technologies. Using R to Unlock the Value of Big Data provides an introduction to open source R and describes issues with traditional R and database interaction. The book then offers in-depth coverage of Oracle's strategic R offerings: Oracle R Enterprise, Oracle R Distribution, ROracle, and Oracle R Connector for Hadoop. You can practice your new skills using the end-of-chapter exercises.

Big Data
Corruption policière Le 5e pouvoir de la blogosphère est tout à fait évident. Démocratie directe. D'une certaine manière nous nous sommes affranchi de la classe politique actuelle qui sont dans l'incompétence et l'outrance la plus absolue. Dans le calme le plus total nous expliquons avec les informations dont nous disposons des incohérences politiques et que des parasites font de la politique de père en fils comme feu Pierre Gosnat à Ivry sur Seine qui était tout ce qu'on voulait sauf un communiste. Le big data pour expliquer tranquillement tout cela est absolument idéal et laisse une liberté de ton indéniable.

Big Data
Den Umgang mit dem Zahlenwust ist der Controller schon heute gewohnt. Big Data könnte die Menge der zu verarbeitenden Kennzahlen allerdings noch einmal stark erhöhen.

Big Data
What do you do when a data set seems too large or complex to handle? In this book, students will learn how the collection and use of data plays an important role in projects of all kinds. Fun, engaging text introduces readers to new ideas and builds on concepts they may already know. Additional tools, including a glossary and an index, help students learn new vocabulary and locate information.

Big Data
Rodion Alukhanov beschäftigt sich in diesem shortcut mit der Datenverarbeitung in der Java-Softwareentwicklung. In diesem Zuge geht er auf verschiedene Dateiformate ein und betrachtet die Herausforderungen der Verarbeitung groBer Datenmengen. Der Autor weist auf die Besonderheiten der Datenverarbeitung in Big-Data-Umgebungen im Vergleich zu klassischen Content-Management-Systemen hin und stellt die Funktionalität von SQL Servern vor. AuBerdem betrachtet er die Message-oriented Middleware (MOM), die zu den Grundtechnologien in der Big-Data-Welt zählt.

Praxishandbuch Big Data
Dieses Praxishandbuch bietet einen Überblick der möglichen Anwendungsfelder und der rechtlichen Rahmenbedingungen von Big Data im Unternehmen. Im ersten Teil wird gezeigt, wie Entscheidungsprozesse mit Daten fundiert werden können und welche Anwendungsmöglichkeiten in verschiedenen Branchen denkbar sind. Der zweite Teil behandelt die rechtlichen Aspekte von Big Data. Die Autoren geben praktische Empfehlungen, wie Big Data-Anwendungen nach geltendem Recht umgesetzt werden können und dabei den technischen und organisatorischen Aufwand so gering wie möglich zu halten. Auch wird erläutert, wie Unternehmen ihre Datenbestände schützen können. Der dritte Teil beschäftigt sich mit den technischen Voraussetzungen von Big Data-Anwendungen.

Big Data Baseball
New York Times BestsellerAfter twenty consecutive losing seasons for the Pittsburgh Pirates, team morale was low, the club's payroll ranked near the bottom of the sport, game attendance was down, and the city was becoming increasingly disenchanted with its team. Pittsburghers joked their town was the city of champions…and the Pirates. Big Data Baseball is the story of how the 2013 Pirates, mired in the longest losing streak in North American pro sports history, adopted drastic big-data strategies to end the drought, make the playoffs, and turn around the franchise's fortunes. Award-winning journalist Travis Sawchik takes you behind the scenes to expertly weave together the stories of the key figures who changed the way the small-market Pirates played the game. For manager Clint Hurdle and the front office staff to save their jobs, they could not rely on a free agent spending spree, instead they had to improve the sum of their parts and find hidden value. They had to change. From Hurdle shedding his old-school ways to work closely with Neal Huntington, the forward-thinking data-driven GM and his team of talented analysts; to pitchers like A.J. Burnett and Gerrit Cole changing what and where they threw; to Russell Martin, the undervalued catcher whose expert use of the nearly-invisible skill of pitch framing helped the team's pitchers turn more balls into strikes; to Clint Barmes, a solid shortstop and one of the early adopters of the unconventional on-field shift which forced the entire infield to realign into positions they never stood in before. Under Hurdle's leadership, a culture of collaboration and creativity flourished as he successfully blended whiz kid analysts with graybeard coaches-a kind of symbiotic teamwork which was unique to the sport. Big Data Baseball is Moneyball on steroids. It is an entertaining and enlightening underdog story that uses the 2013 Pirates season as the perfect lens to examine the sport's burgeoning big-data movement. With the help

Big Data
Convert the promise of big data into real world results There is so much buzz around big data. We all need to know what it is and how it works - that much is obvious. But is a basic understanding of the theory enough to hold your own in strategy meetings? Probably. But what will set you apart from the rest is actually knowing how to USE big data to get solid, real-world business results - and putting that in place to improve performance. Big Data will give you a clear understanding, blueprint, and step-by-step approach to building your own big data strategy. This is a well-needed practical introduction to actually putting the topic into practice. Illustrated with numerous real-world examples from a cross section of companies and organisations, Big Data will take you through the five steps of the SMART model: Start with Strategy, Measure Metrics and Data, Apply Analytics, Report Results, Transform. Discusses how companies need to clearly define what it is they need to know Outlines how companies can collect relevant data and measure the metrics that will help them answer their most important business questions Addresses how the results of big data analytics can be visualised and communicated to ensure key decisions-makers understand them Includes many high-profile case studies from the author's work with some of the world's best known brands

Big Data
Is the Brexit vote successful big data politics or the end of democracy? Why do airlines overbook, and why do banks get it wrong so often? How does big data enable Netflix to forecast a hit, CERN to find the Higgs boson and medics to discover if red wine really is good for you? And how are companies using big data to benefit from smart meters, use advertising that spies on you and develop the gig economy, where workers are managed by the whim of an algorithm? The volumes of data we now access can give unparalleled abilities to make predictions, respond to customer demand and solve problems. But Big Brother's shadow hovers over it. Though big data can set us free and enhance our lives, it has the potential to create an underclass and a totalitarian state. With big data ever-present, you can't afford to ignore it. Acclaimed science writer Brian Clegg - a habitual early adopter of new technology (and the owner of the second-ever copy of Windows in the UK) - brings big data to life.

Big Data and Smart Service Systems
Big Data and Smart Service Systems presents the theories and applications regarding Big Data and smart service systems, data acquisition, smart cities, business decision-making support, and smart service design. The rapid development of computer and Internet technologies has led the world to the era of Big Data. Big Data technologies are widely used, which has brought unprecedented impacts on traditional industries and lifestyle. More and more governments, business sectors, and institutions begin to realize data is becoming the most valuable asset and its analysis is becoming the core competitiveness. Describes the frontier of service science and motivates a discussion among readers on a multidisciplinary subject areas that explores the design of smart serviceIllustrates the concepts, framework, and application of big data and smart service systemsDemonstrates the crucial role of smart service to promote the transformation of the regional and global economy

Big Data
The digital age has presented an exponential growth in the amount of data available to individuals looking to draw conclusions based on given or collected information across industries. Challenges associated with the analysis, security, sharing, storage, and visualization of large and complex data sets continue to plague data scientists and analysts alike as traditional data processing applications struggle to adequately manage big data. Big Data: Concepts, Methodologies, Tools, and Applications is a multi-volume compendium of research-based perspectives and solutions within the realm of large-scale and complex data sets. Taking a multidisciplinary approach, this publication presents exhaustive coverage of crucial topics in the field of big data including diverse applications, storage solutions, analysis techniques, and methods for searching and transferring large data sets, in addition to security issues. Emphasizing essential research in the field of data science, this publication is an ideal reference source for data analysts, IT professionals, researchers, and academics.

Big Data in Practice
The best-selling author of Big Data is back, this time with a unique and in-depth insight into how specific companies use big data. Big data is on the tip of everyone's tongue. Everyone understands its power and importance, but many fail to grasp the actionable steps and resources required to utilise it effectively. This book fills the knowledge gap by showing how major companies are using big data every day, from an up-close, on-the-ground perspective. From technology, media and retail, to sport teams, government agencies and financial institutions, learn the actual strategies and processes being used to learn about customers, improve manufacturing, spur innovation, improve safety and so much more. Organised for easy dip-in navigation, each chapter follows the same structure to give you the information you need quickly. For each company profiled, learn what data was used, what problem it solved and the processes put it place to make it practical, as well as the technical details, challenges and lessons learned from each unique scenario. Learn how predictive analytics helps Amazon, Target, John Deere and Apple understand their customers Discover how big data is behind the success of Walmart, LinkedIn, Microsoft and more Learn how big data is changing medicine, law enforcement, hospitality, fashion, science and banking Develop your own big data strategy by accessing additional reading materials at the end of each chapter

Big Data Fun Facts
Do you know that data is growing faster than ever before and by the year 2020, about 1.7 megabytes of new information will be created every second for every human being on the planet? Interesting, isn't it? Know more about Big Data by reading this ebook. Happy reading!

Big Data in History
Big Data in History introduces the project to create a world-historical archive, tracing the last four centuries of historical dynamics and change. Chapters address the archive's overall plan, how to interpret the past through a global archive, the missions of gathering records, linking local data into global patterns, and exploring the results.

Big Data 2
Ouvrage de 364 pages, actualité anti corruption sur la commune d'Ivry sur Seine et en Val de marne 94 France. Il s'agit d'un recueil d'articles concentré sur des pleines pages word sur la pédophilie et la corruption des tribunaux de commerce.
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