Disruptive Analytics

Disruptive Analytics

Disruptive Analytics

Learn all you need to know about seven key innovations disrupting business analytics today. These innovations—the open source business model, cloud analytics, the Hadoop ecosystem, Spark and in-memory analytics, streaming analytics, Deep Learning, and self-service analytics—are radically changing how businesses use data for competitive advantage. Taken together, they are disrupting the business analytics value chain, creating new opportunities. Enterprises who seize the opportunity will thrive and prosper, while others struggle and decline: disrupt or be disrupted. Disruptive Business Analytics provides strategies to profit from disruption. It shows you how to organize for insight, build and provision an open source stack, how to practice lean data warehousing, and how to assimilate disruptive innovations into an organization. Through a short history of business analytics and a detailed survey of products and services, analytics authority Thomas W. Dinsmore provides a practical explanation of the most compelling innovations available today. What You'll Learn Discover how the open source business model works and how to make it work for you See how cloud computing completely changes the economics of analytics Harness the power of Hadoop and its ecosystem Find out why Apache Spark is everywhere Discover the potential of streaming and real-time analytics Learn what Deep Learning can do and why it matters See how self-service analytics can change the way organizations do business Who This Book Is For Corporate actors at all levels of responsibility for analytics: analysts, CIOs, CTOs, strategic decision makers, managers, systems architects, technical marketers, product developers, IT personnel, and consultants.

Future Trends of HPC in a Disruptive Scenario

Future Trends of HPC in a Disruptive Scenario

Future Trends of HPC in a Disruptive Scenario

The realization that the use of components off the shelf (COTS) could reduce costs sparked the evolution of the massive parallel computing systems available today. The main problem with such systems is the development of suitable operating systems, algorithms and application software that can utilise the potential processing power of large numbers of processors. As a result, systems comprising millions of processors are still limited in the applications they can efficiently solve. Two alternative paradigms that may offer a solution to this problem are Quantum Computers (QC) and Brain Inspired Computers (BIC). This book presents papers from the 14th edition of the biennial international conference on High Performance Computing - From Clouds and Big Data to Exascale and Beyond, held in Cetraro, Italy, from 2 - 6 July 2018. It is divided into 4 sections covering data science, quantum computing, high-performance computing, and applications. The papers presented during the workshop covered a wide spectrum of topics on new developments in the rapidly evolving supercomputing field – including QC and BIC – and a selection of contributions presented at the workshop are included in this volume. In addition, two papers presented at a workshop on Brain Inspired Computing in 2017 and an overview of work related to data science executed by a number of universities in the USA, parts of which were presented at the 2018 and previous workshops, are also included. The book will be of interest to all those whose work involves high-performance computing.

Multimedia Data Mining and Analytics

Multimedia Data Mining and Analytics

Multimedia Data Mining and Analytics

This book provides fresh insights into the cutting edge of multimedia data mining, reflecting how the research focus has shifted towards networked social communities, mobile devices and sensors. The work describes how the history of multimedia data processing can be viewed as a sequence of disruptive innovations. Across the chapters, the discussion covers the practical frameworks, libraries, and open source software that enable the development of ground-breaking research into practical applications. Features: reviews how innovations in mobile, social, cognitive, cloud and organic based computing impacts upon the development of multimedia data mining; provides practical details on implementing the technology for solving real-world problems; includes chapters devoted to privacy issues in multimedia social environments and large-scale biometric data processing; covers content and concept based multimedia search and advanced algorithms for multimedia data representation, processing and visualization.

Disruptive Technology Enhanced Learning

Disruptive Technology Enhanced Learning

Disruptive Technology Enhanced Learning

This book is about how technologies are used in practice to support learning and teaching in higher education. Despite digitization and e-learning becoming ever-increasingly popular in university teaching settings, this book convincingly argues instead in favour of simple and convenient technologies, thus disrupting traditional patterns of learning, teaching and assessment. Michael Flavin uses Disruptive Innovation theory, Activity Theory and the Community of Practice theory as lenses through which to examine technology enhanced learning. This book will be of great interest to all academics with teaching responsibilities, as it illuminates how technologies are used in practice, and is also highly relevant to postgraduate students and researchers in education and technology enhanced learning. It will be especially valuable to leaders and policy-makers in higher education, as it provides insights to inform decision-making on technology enhanced learning at both an institutional and sectoral level.

Disruptive and Emerging Technology Trends Across Education and the Workplace

Disruptive and Emerging Technology Trends Across Education and the Workplace

Disruptive and Emerging Technology Trends Across Education and the Workplace

Advancing technologies are rapidly modifying the current state of business and society causing an expansion of possible career opportunities. In order to stay competitive, institutions of education must provide an emphasis on the wide-range of skills and experiences needed to contribute to a 21st century workforce. As new technologies emerge and even disrupt, there will be a demand for new forms of education and deeper learning. Disruptive and Emerging Technology Trends Across Education and the Workplace is a collection of innovative research on the latest instructive methods being utilized in classrooms and organizations as well as the benefits and challenges of adopting these technologies. While highlighting topics including mobile learning, augmented reality, and cryptocurrencies, this book is ideally designed for developers, professionals, educators, managers, researchers, scientists, stakeholders, strategists, practitioners, and students seeking current research on new forms of educational techniques in relation to the continued application of new technologies in the workplace.

Big Data Big Analytics

Big Data  Big Analytics

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.

Big Data Analytics

Big Data Analytics

Big Data Analytics

Bringing a practitioner’s view to big data analytics, this work examines the drivers behind big data, postulates a set of use cases, identifies sets of solution components, and recommends various implementation approaches. This work also addresses and thoroughly answers key questions on this emerging topic, including What is big data and how is it being used? How can strategic plans for big data analytics be generated? and How does big data change analytics architecture? The author, who has more than 20 years of experience in information management architecture and delivery, has drawn the material from a large breadth of workshops and interviews with business and information technology leaders, providing readers with the latest in evolutionary, revolutionary, and hybrid methodologies of moving forward to the brave new world of big data.

Making Human Capital Analytics Work Measuring the ROI of Human Capital Processes and Outcomes

Making Human Capital Analytics Work  Measuring the ROI of Human Capital Processes and Outcomes

Making Human Capital Analytics Work Measuring the ROI of Human Capital Processes and Outcomes

PROVE THE VALUE OF YOUR HR PROGRAM WITH HARD DATA While corporate leaders may well know the value of human capital, they don’t always understand the extent to which the HR function contributes to the bottom line. So when times get tough and business budgets get cut, HR departments often take the first hit. In this groundbreaking guide, the cofounders of ROI Institute, Jack Phillips and Patti Phillips, provide the tools and techniques you need to use analytics to show top decision makers the value of HR in your organization. Focusing on three types of analytics--descriptive, predictive, and prescriptive--Making Human Capital Analytics Work shows how you can apply analytics by: Developing relationships between variables Predicting the success of HR programs Determining the cost of intangibles that are otherwise diffi cult to value Showing the business value of particular HR programs Calculating and forecasting the ROI of various HR projects and programs Much more than a guide to using data collection and analysis, Making Human Capital Analytics Work is a template for spearheading large-scale change in your organization by dramatically influencing your department's overall image within the organization. The authors take you step-by-step through the processes of using hard data to drive decisions and demonstrate the tangible value of HR. You know that your department is more than administrative and transactional--that it's an integral player in your company's strategy. Apply the lessons in Making Human Capital Analytics Work and ensure that all other stakeholders know too.

AI and Big Data s Potential for Disruptive Innovation

AI and Big Data   s Potential for Disruptive Innovation

AI and Big Data s Potential for Disruptive Innovation

Big data and artificial intelligence (AI) are at the forefront of technological advances that represent a potential transformational mega-trend—a new multipolar and innovative disruption. These technologies, and their associated management paradigm, are already rapidly impacting many industries and occupations, but in some sectors, the change is just beginning. Innovating ahead of emerging technologies is the new imperative for any organization that aspires to succeed in the next decade. Faced with the power of this AI movement, it is imperative to understand the dynamics and new codes required by the disruption and to adapt accordingly. AI and Big Data’s Potential for Disruptive Innovation provides emerging research exploring the theoretical and practical aspects of successfully implementing new and innovative technologies in a variety of sectors including business, transportation, and healthcare. Featuring coverage on a broad range of topics such as semantic mapping, ethics in AI, and big data governance, this book is ideally designed for IT specialists, industry professionals, managers, executives, researchers, scientists, and engineers seeking current research on the production of new and innovative mechanization and its disruptions.

Blockchain Data Analytics For Dummies

Blockchain Data Analytics For Dummies

Blockchain Data Analytics For Dummies

Get ahead of the curve—learn about big data on the blockchain Blockchain came to prominence as the disruptive technology that made cryptocurrencies work. Now, data pros are using blockchain technology for faster real-time analysis, better data security, and more accurate predictions. Blockchain Data Analytics For Dummies is your quick-start guide to harnessing the potential of blockchain. Inside this book, technologists, executives, and data managers will find information and inspiration to adopt blockchain as a big data tool. Blockchain expert Michael G. Solomon shares his insight on what the blockchain is and how this new tech is poised to disrupt data. Set your organization on the cutting edge of analytics, before your competitors get there! Learn how blockchain technologies work and how they can integrate with big data Discover the power and potential of blockchain analytics Establish data models and quickly mine for insights and results Create data visualizations from blockchain analysis Discover how blockchains are disrupting the data world with this exciting title in the trusted For Dummies line!