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Clarisse Dhaenens Metaheuristics for Big Data


Big Data is a new field, with many technological challenges to be understood in order to use it to its full potential. These challenges arise at all stages of working with Big Data, beginning with data generation and acquisition. The storage and management phase presents two critical challenges: infrastructure, for storage and transportation, and conceptual models. Finally, to extract meaning from Big Data requires complex analysis. Here the authors propose using metaheuristics as a solution to these challenges; they are first able to deal with large size problems and secondly flexible and therefore easily adaptable to different types of data and different contexts. The use of metaheuristics to overcome some of these data mining challenges is introduced and justified in the first part of the book, alongside a specific protocol for the performance evaluation of algorithms. An introduction to metaheuristics follows. The second part of the book details a number of data mining tasks, including clustering, association rules, supervised classification and feature selection, before explaining how metaheuristics can be used to deal with them. This book is designed to be self-contained, so that readers can understand all of the concepts discussed within it, and to provide an overview of recent applications of metaheuristics to knowledge discovery problems in the context of Big Data.

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Christopher Price Microsoft Big Data Solutions


Tap the power of Big Data with Microsoft technologies Big Data is here, and Microsoft's new Big Data platform is a valuable tool to help your company get the very most out of it. This timely book shows you how to use HDInsight along with HortonWorks Data Platform for Windows to store, manage, analyze, and share Big Data throughout the enterprise. Focusing primarily on Microsoft and HortonWorks technologies but also covering open source tools, Microsoft Big Data Solutions explains best practices, covers on-premises and cloud-based solutions, and features valuable case studies. Best of all, it helps you integrate these new solutions with technologies you already know, such as SQL Server and Hadoop. Walks you through how to integrate Big Data solutions in your company using Microsoft's HDInsight Server, HortonWorks Data Platform for Windows, and open source tools Explores both on-premises and cloud-based solutions Shows how to store, manage, analyze, and share Big Data through the enterprise Covers topics such as Microsoft's approach to Big Data, installing and configuring HortonWorks Data Platform for Windows, integrating Big Data with SQL Server, visualizing data with Microsoft and HortonWorks BI tools, and more Helps you build and execute a Big Data plan Includes contributions from the Microsoft and HortonWorks Big Data product teams If you need a detailed roadmap for designing and implementing a fully deployed Big Data solution, you'll want Microsoft Big Data Solutions.

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Frank Ohlhorst J. Big Data Analytics. Turning Big Data into Big Money


Unique insights to implement big data analytics and reap big returns to your bottom line Focusing on the business and financial value of big data analytics, respected technology journalist Frank J. Ohlhorst shares his insights on the newly emerging field of big data analytics in Big Data Analytics. This breakthrough book demonstrates the importance of analytics, defines the processes, highlights the tangible and intangible values and discusses how you can turn a business liability into actionable material that can be used to redefine markets, improve profits and identify new business opportunities. Reveals big data analytics as the next wave for businesses looking for competitive advantage Takes an in-depth look at the financial value of big data analytics Offers tools and best practices for working with big data Once the domain of large on-line retailers such as eBay and Amazon, big data is now accessible by businesses of all sizes and across industries. From how to mine the data your company collects, to the data that is available on the outside, Big Data Analytics shows how you can leverage big data into a key component in your business's growth strategy.

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Hyunjoung Lee Fundamentals of Big Data Network Analysis for Research and Industry


Fundamentals of Big Data Network Analysis for Research and Industry Hyunjoung Lee, Institute of Green Technology, Yonsei University, Republic of Korea Il Sohn, Material Science and Engineering, Yonsei University, Republic of Korea Presents the methodology of big data analysis using examples from research and industry There are large amounts of data everywhere, and the ability to pick out crucial information is increasingly important. Contrary to popular belief, not all information is useful; big data network analysis assumes that data is not only large, but also meaningful, and this book focuses on the fundamental techniques required to extract essential information from vast datasets. Featuring case studies drawn largely from the iron and steel industries, this book offers practical guidance which will enable readers to easily understand big data network analysis. Particular attention is paid to the methodology of network analysis, offering information on the method of data collection, on research design and analysis, and on the interpretation of results. A variety of programs including UCINET, NetMiner, R, NodeXL, and Gephi for network analysis are covered in detail. Fundamentals of Big Data Network Analysis for Research and Industry looks at big data from a fresh perspective, and provides a new approach to data analysis. This book: Explains the basic concepts in understanding big data and filtering meaningful data Presents big data analysis within the networking perspective Features methodology applicable to research and industry Describes in detail the social relationship between big data and its implications Provides insight into identifying patterns and relationships between seemingly unrelated big data Fundamentals of Big Data Network Analysis for Research and Industry will prove a valuable resource for analysts, research engineers, industrial engineers, marketing professionals, and any individuals dealing with accumulated large data whose interest is to analyze and identify potential relationships among data sets.

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Marcia Kaufman Big Data For Dummies


Find the right big data solution for your business or organization Big data management is one of the major challenges facing business, industry, and not-for-profit organizations. Data sets such as customer transactions for a mega-retailer, weather patterns monitored by meteorologists, or social network activity can quickly outpace the capacity of traditional data management tools. If you need to develop or manage big data solutions, you'll appreciate how these four experts define, explain, and guide you through this new and often confusing concept. You'll learn what it is, why it matters, and how to choose and implement solutions that work. Effectively managing big data is an issue of growing importance to businesses, not-for-profit organizations, government, and IT professionals Authors are experts in information management, big data, and a variety of solutions Explains big data in detail and discusses how to select and implement a solution, security concerns to consider, data storage and presentation issues, analytics, and much more Provides essential information in a no-nonsense, easy-to-understand style that is empowering Big Data For Dummies cuts through the confusion and helps you take charge of big data solutions for your organization.

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Bill Schmarzo Big Data. Understanding How Data Powers Big Business


Leverage big data to add value to your business Social media analytics, web-tracking, and other technologies help companies acquire and handle massive amounts of data to better understand their customers, products, competition, and markets. Armed with the insights from big data, companies can improve customer experience and products, add value, and increase return on investment. The tricky part for busy IT professionals and executives is how to get this done, and that's where this practical book comes in. Big Data: Understanding How Data Powers Big Business is a complete how-to guide to leveraging big data to drive business value. Full of practical techniques, real-world examples, and hands-on exercises, this book explores the technologies involved, as well as how to find areas of the organization that can take full advantage of big data. Shows how to decompose current business strategies in order to link big data initiatives to the organization’s value creation processes Explores different value creation processes and models Explains issues surrounding operationalizing big data, including organizational structures, education challenges, and new big data-related roles Provides methodology worksheets and exercises so readers can apply techniques Includes real-world examples from a variety of organizations leveraging big data Big Data: Understanding How Data Powers Big Business is written by one of Big Data's preeminent experts, William Schmarzo. Don't miss his invaluable insights and advice.

2875.93 RUR

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Alan Anderson Statistics for Big Data For Dummies


The fast and easy way to make sense of statistics for big data Does the subject of data analysis make you dizzy? You've come to the right place! Statistics For Big Data For Dummies breaks this often-overwhelming subject down into easily digestible parts, offering new and aspiring data analysts the foundation they need to be successful in the field. Inside, you'll find an easy-to-follow introduction to exploratory data analysis, the lowdown on collecting, cleaning, and organizing data, everything you need to know about interpreting data using common software and programming languages, plain-English explanations of how to make sense of data in the real world, and much more. Data has never been easier to come by, and the tools students and professionals need to enter the world of big data are based on applied statistics. While the word «statistics» alone can evoke feelings of anxiety in even the most confident student or professional, it doesn't have to. Written in the familiar and friendly tone that has defined the For Dummies brand for more than twenty years, Statistics For Big Data For Dummies takes the intimidation out of the subject, offering clear explanations and tons of step-by-step instruction to help you make sense of data mining—without losing your cool. Helps you to identify valid, useful, and understandable patterns in data Provides guidance on extracting previously unknown information from large databases Shows you how to discover patterns available in big data Gives you access to the latest tools and techniques for working in big data If you're a student enrolled in a related Applied Statistics course or a professional looking to expand your skillset, Statistics For Big Data For Dummies gives you access to everything you need to succeed.

1655.01 RUR

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John Tanner F. Analytics and Dynamic Customer Strategy. Big Profits from Big Data


Key decisions determine the success of big data strategy Dynamic Customer Strategy: Big Profits from Big Data is a comprehensive guide to exploiting big data for both business-to-consumer and business-to-business marketing. This complete guide provides a process for rigorous decision making in navigating the data-driven industry shift, informing marketing practice, and aiding businesses in early adoption. Using data from a five-year study to illustrate important concepts and scenarios along the way, the author speaks directly to marketing and operations professionals who may not necessarily be big data savvy. With expert insight and clear analysis, the book helps eliminate paralysis-by-analysis and optimize decision making for marketing performance. Nearly seventy-five percent of marketers plan to adopt a big data analytics solution within two years, but many are likely to fail. Despite intensive planning, generous spending, and the best intentions, these initiatives will not succeed without a manager at the helm who is capable of handling the nuances of big data projects. This requires a new way of marketing, and a new approach to data. It means applying new models and metrics to brand new consumer behaviors. Dynamic Customer Strategy clarifies the situation, and highlights the key decisions that have the greatest impact on a company's big data plan. Topics include: Applying the elements of Dynamic Customer Strategy Acquiring, mining, and analyzing data Metrics and models for big data utilization Shifting perspective from model to customer Big data is a tremendous opportunity for marketers and may just be the only factor that will allow marketers to keep pace with the changing consumer and thus keep brands relevant at a time of unprecedented choice. But like any tool, it must be wielded with skill and precision. Dynamic Customer Strategy: Big Profits from Big Data helps marketers shape a strategy that works.

3595.81 RUR

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Jason Williamson Getting a Big Data Job For Dummies


Hone your analytic talents and become part of the next big thing Getting a Big Data Job For Dummies is the ultimate guide to landing a position in one of the fastest-growing fields in the modern economy. Learn exactly what «big data» means, why it's so important across all industries, and how you can obtain one of the most sought-after skill sets of the decade. This book walks you through the process of identifying your ideal big data job, shaping the perfect resume, and nailing the interview, all in one easy-to-read guide. Companies from all industries, including finance, technology, medicine, and defense, are harnessing massive amounts of data to reap a competitive advantage. The demand for big data professionals is growing every year, and experts forecast an estimated 1.9 million additional U.S. jobs in big data by 2015. Whether your niche is developing the technology, handling the data, or analyzing the results, turning your attention to a career in big data can lead to a more secure, more lucrative career path. Getting a Big Data Job For Dummies provides an overview of the big data career arc, and then shows you how to get your foot in the door with topics like: The education you need to succeed The range of big data career path options An overview of major big data employers A plan to develop your job-landing strategy Your analytic inclinations may be your ticket to long-lasting success. In a highly competitive job market, developing your data skills can create a situation where you pick your employer rather than the other way around. If you're ready to get in on the ground floor of the next big thing, Getting a Big Data Job For Dummies will teach you everything you need to know to get started today.

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Jared Dean Big Data, Data Mining, and Machine Learning. Value Creation for Business Leaders and Practitioners


With big data analytics comes big insights into profitability Big data is big business. But having the data and the computational power to process it isn't nearly enough to produce meaningful results. Big Data, Data Mining, and Machine Learning: Value Creation for Business Leaders and Practitioners is a complete resource for technology and marketing executives looking to cut through the hype and produce real results that hit the bottom line. Providing an engaging, thorough overview of the current state of big data analytics and the growing trend toward high performance computing architectures, the book is a detail-driven look into how big data analytics can be leveraged to foster positive change and drive efficiency. With continued exponential growth in data and ever more competitive markets, businesses must adapt quickly to gain every competitive advantage available. Big data analytics can serve as the linchpin for initiatives that drive business, but only if the underlying technology and analysis is fully understood and appreciated by engaged stakeholders. This book provides a view into the topic that executives, managers, and practitioners require, and includes: A complete overview of big data and its notable characteristics Details on high performance computing architectures for analytics, massively parallel processing (MPP), and in-memory databases Comprehensive coverage of data mining, text analytics, and machine learning algorithms A discussion of explanatory and predictive modeling, and how they can be applied to decision-making processes Big Data, Data Mining, and Machine Learning provides technology and marketing executives with the complete resource that has been notably absent from the veritable libraries of published books on the topic. Take control of your organization's big data analytics to produce real results with a resource that is comprehensive in scope and light on hyperbole.

4319.29 RUR

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Tony Boobier Analytics for Insurance. The Real Business of Big Data


The business guide to Big Data in insurance, with practical application insight Big Data and Analytics for Insurers is the industry-specific guide to creating operational effectiveness, managing risk, improving financials, and retaining customers. Written from a non-IT perspective, this book focusses less on the architecture and technical details, instead providing practical guidance on translating analytics into target delivery. The discussion examines implementation, interpretation, and application to show you what Big Data can do for your business, with insights and examples targeted specifically to the insurance industry. From fraud analytics in claims management, to customer analytics, to risk analytics in Solvency 2, comprehensive coverage presented in accessible language makes this guide an invaluable resource for any insurance professional. The insurance industry is heavily dependent on data, and the advent of Big Data and analytics represents a major advance with tremendous potential – yet clear, practical advice on the business side of analytics is lacking. This book fills the void with concrete information on using Big Data in the context of day-to-day insurance operations and strategy. Understand what Big Data is and what it can do Delve into Big Data's specific impact on the insurance industry Learn how advanced analytics can revolutionise the industry Bring Big Data out of IT and into strategy, management, marketing, and more Big Data and analytics is changing business – but how? The majority of Big Data guides discuss data collection, database administration, advanced analytics, and the power of Big Data – but what do you actually do with it? Big Data and Analytics for Insurers answers your questions in real, everyday business terms, tailored specifically to the insurance industry's unique needs, challenges, and targets.

7198.82 RUR

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Dominik Ryzko Modern Big Data Architectures


Provides an up-to-date analysis of big data and multi-agent systems The term Big Data refers to the cases, where data sets are too large or too complex for traditional data-processing software. With the spread of new concepts such as Edge Computing or the Internet of Things, production, processing and consumption of this data becomes more and more distributed. As a result, applications increasingly require multiple agents that can work together. A multi-agent system (MAS) is a self-organized computer system that comprises multiple intelligent agents interacting to solve problems that are beyond the capacities of individual agents. Modern Big Data Architectures examines modern concepts and architecture for Big Data processing and analytics. This unique, up-to-date volume provides joint analysis of big data and multi-agent systems, with emphasis on distributed, intelligent processing of very large data sets. Each chapter contains practical examples and detailed solutions suitable for a wide variety of applications. The author, an internationally-recognized expert in Big Data and distributed Artificial Intelligence, demonstrates how base concepts such as agent, actor, and micro-service have reached a point of convergence—enabling next generation systems to be built by incorporating the best aspects of the field. This book: Illustrates how data sets are produced and how they can be utilized in various areas of industry and science Explains how to apply common computational models and state-of-the-art architectures to process Big Data tasks Discusses current and emerging Big Data applications of Artificial Intelligence Modern Big Data Architectures: A Multi-Agent Systems Perspective is a timely and important resource for data science professionals and students involved in Big Data analytics, and machine and artificial learning.

4621.74 RUR

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Бернард Марр Big Data For Small Business For Dummies


Capitalise on big data to add value to your small business Written by bestselling author and big data expert Bernard Marr, Big Data For Small Business For Dummies helps you understand what big data actually is—and how you can analyse and use it to improve your business. Free of confusing jargon and complemented with lots of step-by-step guidance and helpful advice, it quickly and painlessly helps you get the most from using big data in a small business. Business data has been around for a long time. Unfortunately, it was trapped away in overcrowded filing cabinets and on archaic floppy disks. Now, thanks to technology and new tools that display complex databases in a much simpler manner, small businesses can benefit from the big data that's been hiding right under their noses. With the help of this friendly guide, you'll discover how to get your hands on big data to develop new offerings, products and services; understand technological change; create an infrastructure; develop strategies; and make smarter business decisions. Shows you how to use big data to make sense of user activity on social networks and customer transactions Demonstrates how to capture, store, search, share, analyse and visualise analytics Helps you turn your data into actionable insights Explains how to use big data to your advantage in order to transform your small business If you're a small business owner or employee, Big Data For Small Business For Dummies helps you harness the hottest commodity on the market today in order to take your company to new heights.

2014.11 RUR

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Факультет Аналитики Big Data


Обучение анализу Big Data с нуля на факультете GeekBrains. Научим анализировать большие данные, предоставим опыт для успешного трудоустройства!

179600 RUR
Факультет Аналитики Big Data GeekBrains

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Jacques Janssen Big Data for Insurance Companies


This book will be a “must” for people who want good knowledge of big data concepts and their applications in the real world, particularly in the field of insurance. It will be useful to people working in finance and to masters students using big data tools. The authors present the bases of big data: data analysis methods, learning processes, application to insurance and position within the insurance market. Individual chapters a will be written by well-known authors in this field.

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Группа авторов Metaheuristics


A unified view of metaheuristics This book provides a complete background on metaheuristics and shows readers how to design and implement efficient algorithms to solve complex optimization problems across a diverse range of applications, from networking and bioinformatics to engineering design, routing, and scheduling. It presents the main design questions for all families of metaheuristics and clearly illustrates how to implement the algorithms under a software framework to reuse both the design and code. Throughout the book, the key search components of metaheuristics are considered as a toolbox for: Designing efficient metaheuristics (e.g. local search, tabu search, simulated annealing, evolutionary algorithms, particle swarm optimization, scatter search, ant colonies, bee colonies, artificial immune systems) for optimization problems Designing efficient metaheuristics for multi-objective optimization problems Designing hybrid, parallel, and distributed metaheuristics Implementing metaheuristics on sequential and parallel machines Using many case studies and treating design and implementation independently, this book gives readers the skills necessary to solve large-scale optimization problems quickly and efficiently. It is a valuable reference for practicing engineers and researchers from diverse areas dealing with optimization or machine learning; and graduate students in computer science, operations research, control, engineering, business and management, and applied mathematics.

12871.49 RUR

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Hamouche Oulhadj Metaheuristics for Robotics

Frédéric Héliodore Metaheuristics for Intelligent Electrical Networks


Intelligence is defined by the ability to optimize, manage and reconcile the currents of physical, economic and even social flows. The strong constraint of immediacy proves to be an opportunity to imagine, propose and deliver solutions on the common basis of optimization techniques. Metaheuristics for Intelligent Electrical Networks analyzes the use of metaheuristics through independent applications but united by the same methodology.

14074.69 RUR

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Группа авторов Analytics and Big Data for Accountants

Lillian Pierson Data Science For Dummies


Discover how data science can help you gain in-depth insight into your business – the easy way! Jobs in data science abound, but few people have the data science skills needed to fill these increasingly important roles. Data Science For Dummies is the perfect starting point for IT professionals and students who want a quick primer on all areas of the expansive data science space. With a focus on business cases, the book explores topics in big data, data science, and data engineering, and how these three areas are combined to produce tremendous value. If you want to pick-up the skills you need to begin a new career or initiate a new project, reading this book will help you understand what technologies, programming languages, and mathematical methods on which to focus. While this book serves as a wildly fantastic guide through the broad, sometimes intimidating field of big data and data science, it is not an instruction manual for hands-on implementation. Here’s what to expect: Provides a background in big data and data engineering before moving on to data science and how it's applied to generate value Includes coverage of big data frameworks like Hadoop, MapReduce, Spark, MPP platforms, and NoSQL Explains machine learning and many of its algorithms as well as artificial intelligence and the evolution of the Internet of Things Details data visualization techniques that can be used to showcase, summarize, and communicate the data insights you generate It's a big, big data world out there—let Data Science For Dummies help you harness its power and gain a competitive edge for your organization.

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