The Definitive Guide to Unstructured Data Management and Analysis--From the World’s Leading Information Management Expert A wealth of invaluable information exists in unstructured textual form, but organizations have found it difficult or impossible to access and utilize it. This is changing rapidly: new approaches finally make it possible to glean useful knowledge from virtually any collection of unstructured data. William H. Inmon--the father of data warehousing--and Anthony Nesavich introduce the next data revolution: unstructured data management. Inmon and Nesavich cover all you need to know to make unstructured data work for your organization. You’ll learn how to bring it into your existing structured data environment, leverage existing analytical infrastructure, and implement textual analytic processing technologies to solve new problems and uncover new opportunities. Inmon and Nesavich introduce breakthrough techniques covered in no other book--including the powerful role of textual integration, new ways to integrate textual data into data warehouses, and new SQL techniques for reading and analyzing text. They also present five chapter-length, real-world case studies--demonstrating unstructured data at work in medical research, insurance, chemical manufacturing, contracting, and beyond. This book will be indispensable to every business and technical professional trying to make sense of a large body of unstructured text: managers, database designers, data modelers, DBAs, researchers, and end users alike. Coverage includes What unstructured data is, and how it differs from structured data First generation technology for handling unstructured data, from search engines to ECM--and its limitations Integrating text so it can be analyzed with a common, colloquial vocabulary: integration engines, ontologies, glossaries, and taxonomies Processing semistructured data: uncovering patterns, words, identifiers, and conflicts Novel processing opportunities that arise when text is freed from context Architecture and unstructured data: Data Warehousing 2.0 Building unstructured relational databases and linking them to structured data Visualizations and Self-Organizing Maps (SOMs), including Compudigm and Raptor solutions Capturing knowledge from spreadsheet data and email Implementing and managing metadata: data models, data quality, and more

Exploring how people negotiate and reconcile, construct and re-construct their distinctive gender and ethnic identities in a cross-cultural context, Hu examines what happens when two distinct cultures meet at the intimate interface of marriage and family. Chinese-British Intermarriage reveals how gender and ethnic identities intersect in distinctive ways in shaping the lived experiences of intermarried couples. Through the kaleidoscope of first-generation Chinese-British inter-ethnic families in the UK, the book brings together family, gender, migration and ethnic studies, reflecting on ongoing social processes such as individualisation and globalisation.

Feel confident navigating the fundamentals of data science Data Science Essentials For Dummies is a quick reference on the core concepts of the exploding and in-demand data science field, which involves data collection and working on dataset cleaning, processing, and visualization. This direct and accessible resource helps you brush up on key topics and is right to the point—eliminating review material, wordy explanations, and fluff—so you get what you need, fast. Strengthen your understanding of data science basics Review what you've already learned or pick up key skills Effectively work with data and provide accessible materials to others Jog your memory on the essentials as you work and get clear answers to your questions Perfect for supplementing classroom learning, reviewing for a certification, or staying knowledgeable on the job, Data Science Essentials For Dummies is a reliable reference that's great to keep on hand as an everyday desk reference.

This IBM® Redbooks® publication provides an introduction to the IBM POWER® processor architecture. It describes the IBM POWER processor and IBM Power SystemsTM servers, highlighting the advantages and benefits of IBM Power Systems servers, IBM AIX®, IBM i, and Linux on Power. This publication showcases typical business scenarios that are powered by Power Systems servers. It provides an introduction to the artificial intelligence (AI) capabilities that IBM Watson® services enable, and how these AI capabilities can be augmented in existing applications by using an agile approach to embed intelligence into every operational process. For each use case, the business benefits of adding Watson services are detailed. This publication gives an overview about each Watson service, and how each one is commonly used in real business scenarios. It gives an introduction to the Watson API explorer, which you can use to try the application programming interfaces (APIs) and their capabilities. The Watson services are positioned against the machine learning capabilities of IBM PowerAI. In this publication, you have a guide about how to set up a development environment on Power Systems servers, a sample code implementation of one of the business cases, and a description of preferred practices to move any application that you develop into production. This publication is intended for technical professionals who are interested in learning about or implementing IBM Watson services on AIX, IBM i, and Linux.

Large data sets arriving at every increasing speeds require a new set of efficient data analysis techniques. Data analytics are becoming an essential component for every organization and technologies such as health care, financial trading, Internet of Things, Smart Cities or Cyber Physical Systems. However, these diverse application domains give rise to new research challenges. In this context, the book provides a broad picture on the concepts, techniques, applications, and open research directions in this area. In addition, it serves as a single source of reference for acquiring the knowledge on emerging Big Data Analytics technologies.

The International Encyclopedia of Communication Theory and Philosophy is the definitive single-source reference work on the subject, with state-of-the-art and in-depth scholarly reflection on key issues from leading international experts. It is available both online and in print. A state-of-the-art and in-depth scholarly reflection on the key issues raised by communication, covering the history, systematics, and practical potential of communication theory Articles by leading experts offer an unprecedented level of accuracy and balance Provides comprehensive, clear entries which are both cross-national and cross-disciplinary in nature The Encyclopedia presents a truly international perspective with authors and positions representing not just Europe and North America, but also Latin America and Asia Published both online and in print Part of The Wiley Blackwell-ICA International Encyclopedias of Communication series, published in conjunction with the International Communication Association. Online version available at www.wileyicaencyclopedia.com

Big Data has strongly influenced official statistics, representing a significant innovation that offers a range of opportunities, challenges and risks for the work of national statistical institutions. The fields of application are wide and important. From these data emerge decisive behavioral aspects for companies, according to many strategic directions. The analysis of data at the government and institutional level is a fundamental enabling factor of the smart city paradigm, which is based on a system of interconnected and monitored services with an IoT logic. Furthermore, Big Data are fundamental in the diagnostic and forecasting processes of disease risk. This book aims to lay the essential and train the professional figure of the data scientist, starting from the most basic elements of statistics, a fundamental subject for the explanation of phenomena, up to the explanation and use of complex software such as Python.

Residents in Boston, Massachusetts are automatically reporting potholes and road hazards via their smartphones. Progressive Insurance tracks real-time customer driving patterns and uses that information to offer rates truly commensurate with individual safety. Google accurately predicts local flu outbreaks based upon thousands of user search queries. Amazon provides remarkably insightful, relevant, and timely product recommendations to its hundreds of millions of customers. Quantcast lets companies target precise audiences and key demographics throughout the Web. NASA runs contests via gamification site TopCoder, awarding prizes to those with the most innovative and cost-effective solutions to its problems. Explorys offers penetrating and previously unknown insights into healthcare behavior. How do these organizations and municipalities do it? Technology is certainly a big part, but in each case the answer lies deeper than that. Individuals at these organizations have realized that they don't have to be Nate Silver to reap massive benefits from today's new and emerging types of data. And each of these organizations has embraced Big Data, allowing them to make astute and otherwise impossible observations, actions, and predictions. It's time to start thinking big. In Too Big to Ignore, recognized technology expert and award-winning author Phil Simon explores an unassailably important trend: Big Data, the massive amounts, new types, and multifaceted sources of information streaming at us faster than ever. Never before have we seen data with the volume, velocity, and variety of today. Big Data is no temporary blip of fad. In fact, it is only going to intensify in the coming years, and its ramifications for the future of business are impossible to overstate. Too Big to Ignore explains why Big Data is a big deal. Simon provides commonsense, jargon-free advice for people and organizations looking to understand and leverage Big Data. Rife with case studies, examples, analysis, and quotes from real-world Big Data practitioners, the book is required reading for chief executives, company owners, industry leaders, and business professionals.

This invaluable resource examines the forces behind the explosive growth in data and reveals how the most innovative companies are responding to this challenge. The Internet used to be a tool for telling your customers about your business. Now, it’s real value lies in what it tells you about them. Every move your customers make online can be tracked, catalogued, and analyzed to better understand their preferences and predict their future behavior. With mobile technology like smartphones, customers are online almost every second of every day. The companies that succeed going forward will be those that learn to leverage this torrent of information-without being drowned by it. Data Crush clarifies the key drivers in this emergence, such as: the proliferation of "big data" generated by a never-ending range of online activities (and the mobility that enables much of it); the seemingly infinite array of digital commerce and entertainment pathways; and the rising growth of Cloud computing. These and other factors combine to create an overwhelming universe of valuable information - all constantly updated in real time with billions of mouse clicks each day. It's daunting, but with this onslaught of information comes tremendous opportunity - and Data Crush will help you make sense of it all.

Unstructured data is the most voluminous form of data in the world, and several elements are critical for any advanced analytics practitioner leveraging SAS software to effectively address the challenge of deriving value from that data. This book covers the five critical elements of entity extraction, unstructured data, entity resolution, entity network mapping and analysis, and entity management. By following examples of how to apply processing to unstructured data, readers will derive tremendous long-term value from this book as they enhance the value they realize from SAS products.