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Smart Data statt Big Data
Welche Produkte kann ich meinen Kunden aufgrund ihrer vorherigen Kufe noch anbieten? Wie kann ich meine Abstze vorhersagen oder Kosten optimieren? Wie kann ich Kundenmails automatisch analysieren? Wenn Sie sich diese oder hnliche Fragen stellen, finden Sie in diesem Buch die passenden Antworten. Es richtet sich an alle, die eine gewisse Menge Daten haben und ahnen, dass darin wertvolle Erkenntnisse schlummern, die aber nicht wissen, wie sie sie herauskitzeln knnen. Data-Science-Spezialist John Foreman zeigt Ihnen, wie auch kleinere Unternehmen von Big-Data-Anstzen profitieren und dass Sie dafr nicht mehr bentigen als grundlegende Mathekenntnisse und ein Tabellenkalkulationsprogramm wie Microsoft Excel oder LibreOffice Calc. Nach ein paar ntzlichen allgemeinen Hinweisen zu Excel lernen Sie an realistischen Businessbeispielen, mit welchen Verfahren Sie Kunden clustern, Dokumente klassifizieren, Investitionen und Gewinne optimieren, Prognosen ber zuknftige Abverkufe treffen und wichtige Ausreier identifizieren. Alle Verfahren sind genauso verstndlich wie unterhaltsam erklrt und damit Sie sie direkt selbst ausprobieren knnen, finden Sie alle Beispieldaten zum Download auf der Website des Verlags. Wenn Sie im Anschluss daran noch tiefer in die Datenanalyse einsteigen mchten, zeigt Ihnen ein kurzer Ausblick auf die Programmiersprache R, was noch alles mglich ist. So sind Sie optimal gerstet und holen in Zukunft das Beste aus Ihren Daten heraus!
Category: Mathematics. ISBN: 9783527760602

Data Analytics and Big Data
The main purpose of this book is to investigate, explore and describe approaches and methods to facilitate data understanding through analytics solutions based on its principles, concepts and applications. But analyzing data is also about involving the use of software. For this, and in order to cover some aspect of data analytics, this book uses software (Excel, SPSS, Python, etc) which can help readers to better understand the analytics process in simple terms and supporting useful methods in its application.
Category: Computers. ISBN: 9781786303264

Data Mining and Big Data
This book constitutes the refereed proceedings of the Second International Conference on Data Mining and Big Data, DMBD 2017, held in Fukuoka, Japan, in July/August 2017.  The 53 papers presented in this volume were carefully reviewed and selected from 96 submissions. They were organized in topical sections named: association analysis; clustering; prediction; classification; schedule and sequence analysis; big data; data analysis; data mining; text mining; deep learning; high performance computing; knowledge base and its framework; and fuzzy control. 
Category: Computers. ISBN: 9783319618449

Data Mining and Big Data
This book constitutes the refereed proceedings of the Third International Conference on Data Mining and Big Data, DMBD 2018, held in Shanghai, China, in June 2018. The 74 papers presented in this volume were carefully reviewed and selected from 126 submissions. They are organized in topical sections named: database, data preprocessing, matrix factorization, data analysis, visualization, visibility analysis, clustering, prediction, classification, pattern discovery, text mining and knowledge management, recommendation system in social media, deep learning, big data, Industry 4.0, practical applications
Category: Computers. ISBN: 9783319938028

Big Data, Open Data and Data Development
The world has become digital and technological advances have multiplied circuits with access to data, their processing and their diffusion. New technologies have now reached a certain maturity. Data are available to everyone, anywhere on the planet. The number of Internet users in 2014 was 2.9 billion or 41% of the world population. The need for knowledge is becoming apparent in order to understand this multitude of data. We must educate, inform and train the masses. The development of related technologies, such as the advent of the Internet, social networks, "cloud-computing" (digital factories), has increased the available volumes of data. Currently, each individual creates, consumes, uses digital information: more than 3.4 million e-mails are sent worldwide every second, or 107,000 billion annually with 14,600 e-mails per year per person, but more than 70% are spam. Billions of pieces of content are shared on social networks such as Facebook, more than 2.46 million every minute. We spend more than 4.8 hours a day on the Internet using a computer, and 2.1 hours using a mobile. Data, this new ethereal manna from heaven, is produced in real time. It comes in a continuous stream from a multitude of sources which are generally heterogeneous. This accumulation of data of all types (audio, video, files, photos, etc.) generates new activities, the aim of which is to analyze this enormous mass of information. It is then necessary to adapt and try new approaches, new methods, new knowledge and new ways of working, resulting in new properties and new challenges since SEO logic must be created and implemented. At company level, this mass of data is difficult to manage. Its interpretation is primarily a challenge. This impacts those who are there to "manipulate" the mass and requires a specific infrastructure for creation, storage, processing, analysis and recovery. The biggest challenge lies in "the valuing of data" available in quantity, diversity and access speed.
Category: Technology. ISBN: 9781848218802

Big Data, Smart Data, Stupid Data...
Demain, tout, absolument tout, produira de la data. Les entreprises qui sauront s'en servir russiront. Les autres disparatront. Vous souhaitez dcoller et russir ? Ce livre est fait pour vous ! Pratique et piquant , il vous guidera tape par tape. Pour russir, il vous faut tout bousculer : vos procdures, vos talents, votre culture jusqu' votre proposition de valeur ! Stratgies, excution, casting, contraintes rglementaires ce petit manuel traitera de tout, sans tabou , pour vous permettre d'aller droit au but ! N'attendez plus, lancez-vous !
Category: Business. ISBN: 9782100777471

Principles of Big Data
Principles of Big Data helps readers avoid the common mistakes that endanger all Big Data projects. By stressing simple, fundamental concepts, this book teaches readers how to organize large volumes of complex data, and how to achieve data permanence when the content of the data is constantly changing. General methods for data verification and validation, as specifically applied to Big Data resources, are stressed throughout the book. The book demonstrates how adept analysts can find relationships among data objects held in disparate Big Data resources, when the data objects are endowed with semantic support (i.e., organized in classes of uniquely identified data objects). Readers will learn how their data can be integrated with data from other resources, and how the data extracted from Big Data resources can be used for purposes beyond those imagined by the data creators. Learn general methods for specifying Big Data in a way that is understandable to humans and to computers Avoid the pitfalls in Big Data design and analysis Understand how to create and use Big Data safely and responsibly with a set of laws, regulations and ethical standards that apply to the acquisition, distribution and integration of Big Data resources
Category: Business. ISBN: 9780124045767

Big Data Analytics
Big Data Analytics will assist managers in providing an overview of the drivers for introducing big data technology into the organization and for understanding the types of business problems best suited to big data analytics solutions, understanding the value drivers and benefits, strategic planning, developing a pilot, and eventually planning to integrate back into production within the enterprise. Guides the reader in assessing the opportunities and value proposition Overview of big data hardware and software architectures Presents a variety of technologies and how they fit into the big data ecosystem
Category: Computers. ISBN: 9780124173194

Oracle Big Data Handbook
Transform Big Data into Insight "In this book, some of Oracle's best engineers and architects explain how you can make use of big data. They'll tell you how you can integrate your existing Oracle solutions with big data systems, using each where appropriate and moving data between them as needed." -- Doug Cutting, co-creator of Apache Hadoop Cowritten by members of Oracle's big data team, Oracle Big Data Handbook provides complete coverage of Oracle's comprehensive, integrated set of products for acquiring, organizing, analyzing, and leveraging unstructured data. The book discusses the strategies and technologies essential for a successful big data implementation, including Apache Hadoop, Oracle Big Data Appliance, Oracle Big Data Connectors, Oracle NoSQL Database, Oracle Endeca, Oracle Advanced Analytics, and Oracle's open source R offerings. Best practices for migrating from legacy systems and integrating existing data warehousing and analytics solutions into an enterprise big data infrastructure are also included in this Oracle Press guide. Understand the value of a comprehensive big data strategy Maximize the distributed processing power of the Apache Hadoop platform Discover the advantages of using Oracle Big Data Appliance as an engineered system for Hadoop and Oracle NoSQL Database Configure, deploy, and monitor Hadoop and Oracle NoSQL Database using Oracle Big Data Appliance Integrate your existing data warehousing and analytics infrastructure into a big data architecture Share data among Hadoop and relational databases using Oracle Big Data Connectors Understand how Oracle NoSQL Database integrates into the Oracle Big Data architecture Deliver faster time to value using in-database analytics Analyze data with Oracle Advanced Analytics (Oracle R Enterprise and Oracle Data Mining), Oracle R Distribution, ROracle, and Oracle R Connector for Hadoop Analyze disparate data with Oracle Endeca Information Discovery Plan and implement a big data governance strategy and develop an architecture and roadmap
Category: Computers. ISBN: 9780071827263

Big Data Computing
This book unravels the mystery of Big Data computing and its power to transform business operations. The approach it uses will be helpful to any professional who must present a case for realizing Big Data computing solutions or to those who could be involved in a Big Data computing project. It provides a framework that enables business and technical managers to make optimal decisions necessary for the successful migration to Big Data computing environments and applications within their organizations.
Category: Business. ISBN: 9781498715331
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