Making Sense of Data III: A Practical Guide to Designing Interactive Data Visualizations

PDF | 5.47 MB | 408 pages | English | 2011
Focuses on insights, approaches, and techniques that are essential to designing interactive graphics and visualizations

Making Sense of Data III: A Practical Guide to Designing Interactive Data Visualizations explores a diverse range of disciplines to explain how meaning from graphical representations is extracted. Additionally, the book describes the best approach for designing and implementing interactive graphics and visualizations that play a central role in data exploration and decision-support systems.

Beginning with an introduction to visual perception, Making Sense of Data III features a brief history on the use of visualization in data exploration and an outline of the design process. Subsequent chapters explore the following key areas:

Cognitive and Visual Systems describes how various drawings, maps, and diagrams known as external representations are understood and used to extend the mind's capabilities

Graphics Representations introduces semiotic theory and discusses the seminal work of cartographer Jacques Bertin and the grammar of graphics as developed by Leland Wilkinson

Designing Visual Interactions discusses the four stages of design process—analysis, design, prototyping, and evaluation—and covers the important principles and strategies for designing visual interfaces, information visualizations, and data graphics

Hands-on: Creative Interactive Visualizations with Protovis provides an in-depth explanation of the capabilities of the Protovis toolkit and leads readers through the creation of a series of visualizations and graphics

The final chapter includes step-by-step examples that illustrate the implementation of the discussed methods, and a series of exercises are provided to assist in learning the Protovis language. A related website features the source code for the presented software as well as examples and solutions for select exercises.

Featuring research in psychology, vision science, statistics, and interaction design, Making Sense of Data III is an indispensable book for courses on data analysis and data mining at the upper-undergraduate and graduate levels. The book also serves as a valuable reference for computational statisticians, software engineers, researchers, and professionals of any discipline who would like to understand how the mind processes graphical representations.

DOWNLOAD
Link 1 or Link 2

(On Internet)

Making Sense of Data II: A Practical Guide to Data Visualization, Advanced Data Mining Methods and Applications

PDF | 9 MB | 298 pages | English | 2009
A hands-on guide to making valuable decisions from data using advanced data mining methods and techniques
This second installment in the Making Sense of Data series continues to explore a diverse range of commonly used approaches to making and communicating decisions from data. Delving into more technical topics, this book equips readers with advanced data mining methods that are needed to successfully translate raw data into smart decisions across various fields of research including business, engineering, finance, and the social sciences.

Following a comprehensive introduction that details how to define a problem, perform an analysis, and deploy the results, Making Sense of Data II addresses the following key techniques for advanced data analysis:

Data Visualization reviews principles and methods for understanding and communicating data through the use of visualization including single variables, the relationship between two or more variables, groupings in data, and dynamic approaches to interacting with data through graphical user interfaces.

Clustering outlines common approaches to clustering data sets and provides detailed explanations of methods for determining the distance between observations and procedures for clustering observations. Agglomerative hierarchical clustering, partitioned-based clustering, and fuzzy clustering are also discussed.

Predictive Analytics presents a discussion on how to build and assess models, along with a series of predictive analytics that can be used in a variety of situations including principal component analysis, multiple linear regression, discriminate analysis, logistic regression, and Naïve Bayes.

Applications demonstrates the current uses of data mining across a wide range of industries and features case studies that illustrate the related applications in real-world scenarios.

Each method is discussed within the context of a data mining process including defining the problem and deploying the results, and readers are provided with guidance on when and how each method should be used. The related Web site for the series (www.makingsenseofdata.com) provides a hands-on data analysis and data mining experience. Readers wishing to gain more practical experience will benefit from the tutorial section of the book in conjunction with the TraceisTM software, which is freely available online.

With its comprehensive collection of advanced data mining methods coupled with tutorials for applications in a range of fields, Making Sense of Data II is an indispensable book for courses on data analysis and data mining at the upper-undergraduate and graduate levels. It also serves as a valuable reference for researchers and professionals who are interested in learning how to accomplish effective decision making from data and understanding if data analysis and data mining methods could help their organization.

DOWNLOAD
Link 1 or Link 2

(On Internet)

Making Sense of Data I: A Practical Guide to Exploratory Data Analysis and Data Mining

EPUB | 8.4 MB | 248 pages | English | Glenn J. Myatt | 2014
Making Sense of Data I: A Practical Guide to Exploratory Data Analysis and Data Mining (2nd Edition) by Glenn J. Myatt

A proven go-to guide for data analysis, Making Sense of Data I: A Practical Guide to Exploratory Data Analysis and Data Mining, Second Edition focuses on basic data analysis approaches that are necessary to make timely and accurate decisions in a diverse range of projects. Based on the authors’ practical experience in implementing data analysis and data mining, the new edition provides clear explanations that guide readers from almost every field of study.
In order to facilitate the needed steps when handling a data analysis or data mining project, a step-by-step approach aids professionals in carefully analyzing data and implementing results, leading to the development of smarter business decisions. The tools to summarize and interpret data in order to master data analysis are integrated throughout, and the Second Edition also features:

•Updated exercises for both manual and computer-aided implementation with accompanying worked examples
•New appendices with coverage on the freely available Traceis™ software, including tutorials using data from a variety of disciplines such as the social sciences, engineering, and finance
•New topical coverage on multiple linear regression and logistic regression to provide a range of widely used and transparent approaches
•Additional real-world examples of data preparation to establish a practical background for making decisions from data

Making Sense of Data I: A Practical Guide to Exploratory Data Analysis and Data Mining, Second Edition is an excellent reference for researchers and professionals who need to achieve effective decision making from data. The Second Edition is also an ideal textbook for undergraduate and graduate-level courses in data analysis and data mining and is appropriate for cross-disciplinary courses found within computer science and engineering departments.

DOWNLOAD
Link 1 or Link 2

(On Internet)

Information Systems for Managers: With Cases, Edition 4.0

PDF | 23.7 MB | 1008 pages | English | 2019
Information Systems for Managers offers a general introduction to Information Systems as well as focused coverage of the strategic role of information systems in the modern firm, and the design and implementation of IT-department strategic initiatives. Going beyond just a discussion of concepts, Piccoli & Pigni empowers readers to make critical IS strategy decisions and effectively communicate with IS professionals to ensure the successful implementation of their initiatives. Edition 4.0 has been comprehensively updated with new coverage of big data technologies and cloud computing, blockchain, virtual and augmented reality, machine learning, artificial intelligence, the Process Virtualization Theory, mobile security, fake news, troll factories, and cybersecurity frameworks. This version Includes a set of full-length cases studies.

DOWNLOAD
Google Drive (Pass: shinshinshare)

(Internet Resource)

Inside Blockchain, Bitcoin and Cryptocurrencies

PDF | 23.57 MB | 390 pages | English | 2019
This book covers blockchain from the underlying principles to how it enables applications to survive and surf on its shoulder. Having covered the fundamentals of blockchain, the book turns to cryptocurrency. It thoroughly examines Bitcoin before presenting six other major currencies in a rounded discussion. The book then bridges between technology and finance, concentrating on how blockchain-based applications, including cryptocurrencies, have pushed hard against mainstream industries in a bid to cement their positions permanent. It discusses blockchain as underlying banking technology, crypto mining and offering, cryptocurrency as investment instruments, crypto regulations, and markets.

DOWNLOAD
Google Drive (Pass: shinshinshare)

(Internet Resource)