Using Web and Paper Questionnaires for Data-Based Decision Making

Using Web and Paper Questionnaires for Data-Based Decision Making
Author: Susan J. Thomas
Publisher: Corwin Press
Total Pages: 217
Release: 2004-03-06
Genre: Education
ISBN: 0761938834

Excerpt: ...tribe. He had faculties. He had also various idiosyncrasies. He was undeniably the best hunter and trapper and trainer of dogs to sledge, as well as the most expert upon snowshoes of all the Indians living upon the point, and he was, furthermore, one of the dirtiest of them and the biggest drunkard whenever opportunity afforded. Fortunately for him and for his squaw, Bigbeam, as she had been facetiously named by an agent of the company, the opportunities for getting drunk were rare, for the company is conservative in the distribution of that which makes bad hunters. Given an abundance of firewater and tobacco, Red Dog was the happiest Indian between the northern boundary of the United States and Lake Gary; deprived of them both he hunted vigorously, thinking all the while of the coming hour when, after a long journey and much travail, he should be in what was his idea of heaven again. To-day, though, the rifle bought from the company stood idle beside the ridge-pole, the sledge dogs snarled and fought upon the snow outside, and Bigbeam, squat and broad as became her name, looked askance at her lord as she prepared the moose meat, uncertain of his temper, for his face was cloudy. Red Dog was, in fact, perplexed, and was planning deeply. Good reason was there for Red Dog's thought. Events of the immediate future were of moment to him and all his fellows, among whom, though no chief was formally acknowledged, he was recognized as leader; for had he not at one time been with the company as a hired hunter? Had he not once gone with a fur-carrying party even to Hudson's Bay, and thence to the far south and even to Quebec? And did he not know the ways of the company, and could not he talk a French patois which enabled him to be understood at the stations? Now, as fitting representative of himself and of his clan, a great responsibility had come upon him, and he was lost in as anxious thought as could come to a biped of his quality. Like a more or less...

Science Data Book

Science Data Book
Author: Ralph. M. Tennent
Publisher:
Total Pages: 105
Release: 1971
Genre: Mathematics
ISBN: 9780050024874

Dear Data

Dear Data
Author: Giorgia Lupi
Publisher: Chronicle Books
Total Pages: 304
Release: 2016-09-13
Genre: Design
ISBN: 1616895462

Equal parts mail art, data visualization, and affectionate correspondence, Dear Data celebrates "the infinitesimal, incomplete, imperfect, yet exquisitely human details of life," in the words of Maria Popova (Brain Pickings), who introduces this charming and graphically powerful book. For one year, Giorgia Lupi, an Italian living in New York, and Stefanie Posavec, an American in London, mapped the particulars of their daily lives as a series of hand-drawn postcards they exchanged via mail weekly—small portraits as full of emotion as they are data, both mundane and magical. Dear Data reproduces in pinpoint detail the full year's set of cards, front and back, providing a remarkable portrait of two artists connected by their attention to the details of their lives—including complaints, distractions, phone addictions, physical contact, and desires. These details illuminate the lives of two remarkable young women and also inspire us to map our own lives, including specific suggestions on what data to draw and how. A captivating and unique book for designers, artists, correspondents, friends, and lovers everywhere.

Data

Data
Author:
Publisher:
Total Pages: 710
Release: 1915
Genre:
ISBN:

Large Scale and Big Data

Large Scale and Big Data
Author: Sherif Sakr
Publisher: CRC Press
Total Pages: 640
Release: 2014-06-25
Genre: Computers
ISBN: 1466581506

Large Scale and Big Data: Processing and Management provides readers with a central source of reference on the data management techniques currently available for large-scale data processing. Presenting chapters written by leading researchers, academics, and practitioners, it addresses the fundamental challenges associated with Big Data processing tools and techniques across a range of computing environments. The book begins by discussing the basic concepts and tools of large-scale Big Data processing and cloud computing. It also provides an overview of different programming models and cloud-based deployment models. The book’s second section examines the usage of advanced Big Data processing techniques in different domains, including semantic web, graph processing, and stream processing. The third section discusses advanced topics of Big Data processing such as consistency management, privacy, and security. Supplying a comprehensive summary from both the research and applied perspectives, the book covers recent research discoveries and applications, making it an ideal reference for a wide range of audiences, including researchers and academics working on databases, data mining, and web scale data processing. After reading this book, you will gain a fundamental understanding of how to use Big Data-processing tools and techniques effectively across application domains. Coverage includes cloud data management architectures, big data analytics visualization, data management, analytics for vast amounts of unstructured data, clustering, classification, link analysis of big data, scalable data mining, and machine learning techniques.

Mining of Data with Complex Structures

Mining of Data with Complex Structures
Author: Fedja Hadzic
Publisher: Springer
Total Pages: 340
Release: 2011-02-03
Genre: Computers
ISBN: 3642175570

Mining of Data with Complex Structures: - Clarifies the type and nature of data with complex structure including sequences, trees and graphs - Provides a detailed background of the state-of-the-art of sequence mining, tree mining and graph mining. - Defines the essential aspects of the tree mining problem: subtree types, support definitions, constraints. - Outlines the implementation issues one needs to consider when developing tree mining algorithms (enumeration strategies, data structures, etc.) - Details the Tree Model Guided (TMG) approach for tree mining and provides the mathematical model for the worst case estimate of complexity of mining ordered induced and embedded subtrees. - Explains the mechanism of the TMG framework for mining ordered/unordered induced/embedded and distance-constrained embedded subtrees. - Provides a detailed comparison of the different tree mining approaches highlighting the characteristics and benefits of each approach. - Overviews the implications and potential applications of tree mining in general knowledge management related tasks, and uses Web, health and bioinformatics related applications as case studies. - Details the extension of the TMG framework for sequence mining - Provides an overview of the future research direction with respect to technical extensions and application areas The primary audience is 3rd year, 4th year undergraduate students, Masters and PhD students and academics. The book can be used for both teaching and research. The secondary audiences are practitioners in industry, business, commerce, government and consortiums, alliances and partnerships to learn how to introduce and efficiently make use of the techniques for mining of data with complex structures into their applications. The scope of the book is both theoretical and practical and as such it will reach a broad market both within academia and industry. In addition, its subject matter is a rapidly emerging field that is critical for efficient analysis of knowledge stored in various domains.

Data Analytics and AI

Data Analytics and AI
Author: Jay Liebowitz
Publisher: CRC Press
Total Pages: 242
Release: 2020-08-06
Genre: Computers
ISBN: 1000094650

Analytics and artificial intelligence (AI), what are they good for? The bandwagon keeps answering, absolutely everything! Analytics and artificial intelligence have captured the attention of everyone from top executives to the person in the street. While these disciplines have a relatively long history, within the last ten or so years they have exploded into corporate business and public consciousness. Organizations have rushed to embrace data-driven decision making. Companies everywhere are turning out products boasting that "artificial intelligence is included." We are indeed living in exciting times. The question we need to ask is, do we really know how to get business value from these exciting tools? Unfortunately, both the analytics and AI communities have not done a great job in collaborating and communicating with each other to build the necessary synergies. This book bridges the gap between these two critical fields. The book begins by explaining the commonalities and differences in the fields of data science, artificial intelligence, and autonomy by giving a historical perspective for each of these fields, followed by exploration of common technologies and current trends in each field. The book also readers introduces to applications of deep learning in industry with an overview of deep learning and its key architectures, as well as a survey and discussion of the main applications of deep learning. The book also presents case studies to illustrate applications of AI and analytics. These include a case study from the healthcare industry and an investigation of a digital transformation enabled by AI and analytics transforming a product-oriented company into one delivering solutions and services. The book concludes with a proposed AI-informed data analytics life cycle to be applied to unstructured data.

Afterlives of Data

Afterlives of Data
Author: Mary F.E. Ebeling
Publisher: Univ of California Press
Total Pages: 218
Release: 2022-06-14
Genre: Social Science
ISBN: 0520973828

What our health data tell American capitalism about our value—and how that controls our lives. Afterlives of Data follows the curious and multiple lives that our data live once they escape our control. Mary F. E. Ebeling's ethnographic investigation shows how information about our health and the debt that we carry becomes biopolitical assets owned by healthcare providers, insurers, commercial data brokers, credit reporting companies, and platforms. By delving into the oceans of data built from everyday medical and debt traumas, Ebeling reveals how data about our lives come to affect our bodies and our life chances and to wholly define us. Investigations into secretive data collection and breaches of privacy by the likes of Cambridge Analytica have piqued concerns among many Americans about exactly what is being done with their data. From credit bureaus and consumer data brokers like Equifax and Experian to the secretive military contractor Palantir, this massive industry has little regulatory oversight for health data and works to actively obscure how it profits from our data. In this book, Ebeling traces the health data—medical information extracted from patients' bodies—that are digitized and repackaged into new data commodities that have afterlives in database lakes and oceans, algorithms, and statistical models used to score patients on their creditworthiness and riskiness. Critical and disturbing, Afterlives of Data examines how Americans' data about their health and their debt are used in the service of marketing and capitalist surveillance.