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New Book. Shipped from UK. Established seller since 2000.

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.

New! This book is in the same immaculate condition as when it was published 2.07

Data Science and Big Data Analytics is about harnessing the power of data for new insights. The book covers the breadth of activities and methods and tools that Data Scientists use. The content focuses on concepts, principles and practical applications that are applicable to any industry and technology environment, and the learning is supported and explained with examples that you can replicate using open-source software. This book will help you: Become a contributor on a data science team Deploy a structured lifecycle approach to data analytics problems Apply appropriate analytic techniques and tools to analyzing big data Learn how to tell a compelling story with data to drive business action Prepare for EMC Proven Professional Data Science Certification Corresponding data sets are available at www.wiley.com/go/9781118876138. Get started discovering, analyzing, visualizing, and presenting data in a meaningful way today!

Data Science and Big Data Analytics is about harnessing the power of data for new insights. The book covers the breadth of activities and methods and tools that Data Scientists use. The content focuses on concepts, principles and practical applications that are applicable to any industry and technology environment, and the learning is supported and explained with examples that you can replicate using open-source software. This book will help you: Become a contributor on a data science team Deploy a structured lifecycle approach to data analytics problems Apply appropriate analytic techniques and tools to analyzing big data Learn how to tell a compelling story with data to drive business action Prepare for EMC Proven Professional Data Science Certification Corresponding data sets are available at www.wiley.com/go/9781118876138. Get started discovering, analyzing, visualizing, and presenting data in a meaningful way today!

Simplify Big Data Analytics with Amazon EMR: A beginner's guide to learning and implementing Amazon EMR for building data analytics solutions 1.62

Book is in Used-VeryGood condition. Pages and cover are clean and intact. Used items may not include supplementary materials such as CDs or access codes. May show signs of minor shelf wear and contain very limited notes and highlighting. 0.71

New! This book is in the same immaculate condition as when it was published 0.71

Gain the key language concepts and programming techniques of Scala in the context of big data analytics and Apache Spark. The book begins by introducing you to Scala and establishes a firm contextual understanding of why you should learn this language, how it stands in comparison to Java, and how Scala is related to Apache Spark for big data analytics. Next, you’ll set up the Scala environment ready for examining your first Scala programs. This is followed by sections on Scala fundamentals including mutable/immutable variables, the type hierarchy system, control flow expressions and code blocks.The author discusses functions at length and highlights a number of associated concepts such as functional programming and anonymous functions. The book then delves deeper into Scala’s powerful collections system because many of Apache Spark’s APIs bear a strong resemblance to Scala collections. Along the way you’ll see the development life cycle of a Scala program. This involves compiling and building programs using the industry-standard Scala Build Tool (SBT). You’ll cover guidelines related to dependency management using SBT as this is critical for building large Apache Spark applications.  Scala Programming for Big Data Analytics concludes by demonstrating how you can make use of the concepts to write programs that run on the Apache Spark framework. These programs will provide distributed and parallel computing, which is critical for big data analytics.What You Will LearnSee the fundamentals of Scala as a general-purpose programming languageUnderstand functional programming and object-oriented programming constructs in ScalaUse Scala collections and functions Develop, package and run Apache Spark applications for big data analyticsWho This Book Is ForData scientists, data analysts and data engineers who intend to use Apache Spark for large-scale analytics.

Book is in Used-VeryGood condition. Pages and cover are clean and intact. Used items may not include supplementary materials such as CDs or access codes. May show signs of minor shelf wear and contain very limited notes and highlighting. 0.9

Book is in Used-VeryGood condition. Pages and cover are clean and intact. Used items may not include supplementary materials such as CDs or access codes. May show signs of minor shelf wear and contain very limited notes and highlighting. 1.46

Gain the key language concepts and programming techniques of Scala in the context of big data analytics and Apache Spark. The book begins by introducing you to Scala and establishes a firm contextual understanding of why you should learn this language, how it stands in comparison to Java, and how Scala is related to Apache Spark for big data analytics. Next, you’ll set up the Scala environment ready for examining your first Scala programs. This is followed by sections on Scala fundamentals including mutable/immutable variables, the type hierarchy system, control flow expressions and code blocks.The author discusses functions at length and highlights a number of associated concepts such as functional programming and anonymous functions. The book then delves deeper into Scala’s powerful collections system because many of Apache Spark’s APIs bear a strong resemblance to Scala collections. Along the way you’ll see the development life cycle of a Scala program. This involves compiling and building programs using the industry-standard Scala Build Tool (SBT). You’ll cover guidelines related to dependency management using SBT as this is critical for building large Apache Spark applications.  Scala Programming for Big Data Analytics concludes by demonstrating how you can make use of the concepts to write programs that run on the Apache Spark framework. These programs will provide distributed and parallel computing, which is critical for big data analytics.What You Will LearnSee the fundamentals of Scala as a general-purpose programming languageUnderstand functional programming and object-oriented programming constructs in ScalaUse Scala collections and functions Develop, package and run Apache Spark applications for big data analyticsWho This Book Is ForData scientists, data analysts and data engineers who intend to use Apache Spark for large-scale analytics.

Buy with confidence! Book is in new, never-used condition 0.97

Business Intelligence Strategy in the Big Data Analytics: A General Management Perspective explains how to deliver competitive advantages and substantial economic benefits by overcoming commonly-encountered barriers to success. It includes lessons learned from leading companies that provide practical ideas for how to use the many different forms of BI to meet key business objectives. Further, it clarifies how BI initiatives are really business initiatives that require business units to change how they use information and analysis to drive and improve business results, particularly profits. Business intelligence (BI) and business analytics are like a Swiss army knife-they can be used in many different ways to achieve many different business purposes. In working with leading companies in a wide range of industries to help them formulate and execute BI strategies and program plans, the author has seen firsthand that these successful companies struggle in two key areas: BI Strategy, which is understanding how they can leverage BI in core business functions such as marketing, sales, customer service, operations, distribution, supplier management, cost improvement, and financial management; and BI Program Execution, which is effectively aligning and executing the diverse workstreams that are critical for achieving a return on investment (ROI), including change management, business process and BI integration, and BI and data warehousing development.

Data availability is surpassing existing paradigms for governing, managing, analyzing, and interpreting health data. Big Data and Health Analytics provides frameworks, use cases, and examples that illustrate the role of big data and analytics in modern health care, including how public health information can inform health delivery.Written for health care professionals and executives, this is not a technical book on the use of statistics and machine-learning algorithms for extracting knowledge out of data, nor a book on the intricacies of database design. Instead, this book presents the current thinking of academic and industry researchers and leaders from around the world.Using non-technical language, this book is accessible to health care professionals who might not have an IT and analytics background. It includes case studies that illustrate the business processes underlying the use of big data and health analytics to improve health care delivery.Highlighting lessons learned from the case studies, the book supplies readers with the foundation required for further specialized study in health analytics and data management. Coverage includes community health information, information visualization which offers interactive environments and analytic processes that support exploration of EHR data, the governance structure required to enable data analytics and use, federal regulations and the constraints they place on analytics, and information security.Links to websites, videos, articles, and other online content that expand and support the primary learning objectives for each major section of the book are also included to help you develop the skills you will need to achieve quality improvements in health care delivery through the effective use of data and analytics.

"The chapters in this volume offer useful case studies, technical roadmaps, lessons learned, and a few prescriptions to ‘do this, avoid that.’"―From the Foreword by Joe LaCugna, Ph.D., Enterprise Analytics and Business Intelligence, Starbucks Coffee Company With the growing barrage of "big data," it becomes vitally important for organizations to make sense of this data and information in a timely and effective way. That’s where analytics come into play. Research shows that organizations that use business analytics to guide their decision making are more productive and experience higher returns on equity. Big Data and Business Analytics helps you quickly grasp the trends and techniques of big data and business analytics to make your organization more competitive. Packed with case studies, this book assembles insights from some of the leading experts and organizations worldwide. Spanning industry, government, not-for-profit organizations, and academia, they share valuable perspectives on big data domains such as cybersecurity, marketing, emergency management, healthcare, finance, and transportation. Understand the trends, potential, and challenges associated with big data and business analytics Get an overview of machine learning, advanced statistical techniques, and other predictive analytics that can help you solve big data issues Learn from VPs of Big Data/Insights & Analytics via case studies of Fortune 100 companies, government agencies, universities, and not-for-profits Big data problems are complex. This book shows you how to go from being data-rich to insight-rich, improving your decision making and creating competitive advantage. Author Jay Liebowitz recently had an article published in The World Financial Review. www.worldfinancialreview.com/?p=1904

Data availability is surpassing existing paradigms for governing, managing, analyzing, and interpreting health data. Big Data and Health Analytics provides frameworks, use cases, and examples that illustrate the role of big data and analytics in modern health care, including how public health information can inform health delivery.Written for health care professionals and executives, this is not a technical book on the use of statistics and machine-learning algorithms for extracting knowledge out of data, nor a book on the intricacies of database design. Instead, this book presents the current thinking of academic and industry researchers and leaders from around the world.Using non-technical language, this book is accessible to health care professionals who might not have an IT and analytics background. It includes case studies that illustrate the business processes underlying the use of big data and health analytics to improve health care delivery.Highlighting lessons learned from the case studies, the book supplies readers with the foundation required for further specialized study in health analytics and data management. Coverage includes community health information, information visualization which offers interactive environments and analytic processes that support exploration of EHR data, the governance structure required to enable data analytics and use, federal regulations and the constraints they place on analytics, and information security.Links to websites, videos, articles, and other online content that expand and support the primary learning objectives for each major section of the book are also included to help you develop the skills you will need to achieve quality improvements in health care delivery through the effective use of data and analytics.

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

BRAND NEW, Exactly same ISBN as listed, Please double check ISBN carefully before ordering.

BRAND NEW, Exactly same ISBN as listed, Please double check ISBN carefully before ordering.