Java Data Object

Many people may be unsure of what 'structured data' means, but everyone will recognise it: data that resides within a fixed field in a record. At the same time, the web, mobile and social networks, an

Data mining is an increasingly valuable tool within the institution of higher education. Educational Data Mining (EDM) has emerged as a field in its own right, focusing on data mining techniques

This book introduces fundamentals and trade-offs of data de-duplication techniques. It describes novel emerging de-duplication techniques that remove duplicate data both in storage and network in an e

Generating data is the defining aspect of empirical work. Data in this respect is understood as information-capacitated material that must be discovered, mined, unearthed - or a near limitless range o

This book discusses data privacy in banking and financial services, anonymization principles and practice, test data management, and synthetic data generation. From a practice standpoint, it provides

A systematic introduction to the theory, development and latest research results of radar data processing technology• Presents both classical theory and development methods of radar data processing• P

This book presents cutting edge research on the newethical challenges posed by biomedical Big Data technologies and practices.‘Biomedical Big Data’ refers to the analysis of aggregated, very large dat

Data uncertainty widely exists in many applications, and an uncertain data stream is a series of uncertain tuples that arrive rapidly. However, traditional techniques for deterministic data streams ca

This illuminating text/reference surveys the state of the art in data science, and provides practical guidance on big data analytics. Expert perspectives are provided by authoritative researchers and

This book is about innovation, big data, and data science seen from a business perspective. Big data is a buzzword nowadays, and there is a growing necessity within practitioners to understand better

This book presents and explains the methods utilized to apply techniques from big data to massive structural data sets, especially those relating to the generation and analysis of very large networks

While laboratory research is the backbone of collecting experimental data in cognitive science, a rapidly increasing amount of research is now capitalizing on large-scale and real-world digital data.

Incorporating an innovative focus on data visualization and time series forecasting,Data Mining for Business Intelligence supplies insightful, detailed guidance on fundamental data mining techniques.

From the first tally, scratched on a wolf bone over thirty thousand years ago, to the Large Hadron Collider, which produces forty million megabytes of data per second, data is big, and getting bigger.

This book presents different use cases in big data applications and related practical experiences. Many businesses today are increasingly interested in utilizing big data technologies for supporting t

Big data is a broad term that defines the structured or unstructured data sets. It is a challenging field which includes analysis, transfer and visualization of data. This book presents in-depth descr

This book addresses three challenging issues related to Big Data. First, how do we aggregate heterogeneous types of data from numerous sources and then use fast database management technology to store

This volume details several important databases and data mining tools. Data Mining Techniques for the Life Sciences, Second Editionguides readers through archives of macromolecular three-dimensional s

This is the second edition of Wil van der Aalst’s seminal book on process mining, which now discusses the field also in the broader context of data science and big data approaches. It includes several

Robert John Ackermann deals decisively with the problem of relativism that has plagued post-empiricist philosophy of science. Recognizing that theory and data are mediated by data domains (bordered da

In this book, Helen Kennedy argues that as social media data mining becomes more and more ordinary, as we post, mine and repeat, new data relations emerge. These new data relations are characterised b

This volume covers a large area, from the description of methodologies for data analysis to the real application. Chapters focus on methodologies for preprocessing of microarray data, a survey of miRN

Numerical computation, knowledge discovery and statistical data analysis integrated with powerful 2D and 3D graphics for visualization are the key topics of this book. The Python code examples powered

Designing Data Reports that Work provides research-based best practices for constructing effective data systems in schools and for designing reports that are relevant, necessary, and easily understood

This book covers three major parts of Big Data: concepts, theories and applications. Written by world-renowned leaders in Big Data, this book explores the problems, possible solutions and directi

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 a

Since publication of the bestselling Environmental Data Analysis with MATLABR, many advances have been made in environmental data analysis. This new edition expands fundamentally on the original with

In an era where many believe Big Data has rendered human perception and observation 'old-school' or passe, Martin Lindstrom shows that mining and matching technological data with up-close psychologica

Building Java Programs: A Back to Basics Approach, Third Edition, introduces novice programmers to basic constructs and common pitfalls by emphasizing the essentials of procedural programming, problem

Utilising both key mathematical tools and state-of-the-art research results, this text explores the principles underpinning large-scale information processing over networks and examines the crucial interaction between big data and its associated communication, social and biological networks. Written by experts in the diverse fields of machine learning, optimisation, statistics, signal processing, networking, communications, sociology and biology, this book employs two complementary approaches: first analysing how the underlying network constrains the upper-layer of collaborative big data processing, and second, examining how big data processing may boost performance in various networks. Unifying the broad scope of the book is the rigorous mathematical treatment of the subjects, which is enriched by in-depth discussion of future directions and numerous open-ended problems that conclude each chapter. Readers will be able to master the fundamental principles for dealing with big data over

This book describes current problems in data science and Big Data. Key topics are data classification, Graph Cut, the Laplacian Matrix, Google Page Rank, efficient algorithms, hardness of problems, di

This book introduces two basic big data processing paradigms for batch data and streaming data. Representative programming frameworks are also presented, as well as software defined networking (

Introduction to Statistical Analysis of Laboratory Data presents a detailed discussion of important statistical concepts and methods of data presentation and analysis Provides detailed discussions on

The rapid developments in GIS such as data integration, representation, spatial data products, and new spatial data mining methods, are forcing users to deal with data of unknown or ambiguous quality;

A comprehensive compilation of new developments in data linkage methodology The increasing availability of large administrative databases has led to a dramatic rise in the use of data linkage

“In this comprehensive book, Professor Randy Deutsch has unlocked and laid bare the twenty-first centurycodice nascosto of architecture. It is data. Big data. Data as driver. . .This book offers us th

The amount of data in our world has been exploding, and analyzing large data sets—so called big data—will become a key basis of competition in business. Statisticians and researchers will be updating

Data as a Service shows how organizations can leverage “data as a service” by providing real-life case studies on the various and innovative architectures and related patterns Comprehensive approach

Fills the Existing Gap of Mathematics for Data FusionData fusion (DF) combines large amounts of information from a variety of sources and fuses this data algorithmically, logically and, if required in

Networking and communication are important aspects of big data, especially when real-time or near real-time applications are demanded. For example, the storage of big data depends on distributed syste