Data Data Everywhere

The latest book from best-selling author Victoria L. Bernhardt is an easy-to-read primer that describes what it takes to achieve student learning growth at every grade level, in every subject area, and with every student group.

The latest book from best-selling author Victoria L. Bernhardt is an easy-to-read primer that describes what it takes to achieve student learning growth at every grade level, in every subject area, and with every student group. In this new edition, readers will learn how to use data to inform their continuous school improvement as they develop an appreciation of the various types of data, uses for data, and how data are involved in the process. This accessible, updated edition provides a wealth of straightforward and accessible strategies that will allow educators to become comfortable with the many uses of data in increasing student improvement. Data, Data Everywhere, 2nd edition, provides a framework and summary of the continuous school improvement framework. It is a perfect resource for teachers, administrators, support staff, and students of leadership to guide comprehensive school improvement that will make a difference for all students.

This book features the refereed proceedings from the 24th British National Conference on Databases, held in Glasgow, Scotland in July 2007. The eighteen full papers and seven poster papers are presented, together with two invited contributions. Papers are organized into topical sections covering data applications, searching XML documents, querying XML documents, XML transformation, clustering and security, data mining, and extraction.

Hospitals, doctors' offices, and pharmacies are sitting on some very valuable information - your medical information. As health-care providers enter the digital world and computerize their patients' records in an effort to improve the efficiency and quality of care, they are also building a valuable health research tool. The files in their databases may contain the answers to many medical questions we currently face, but they also contain private information that could potentially be misused.Data Data Everywherehighlights the challenges that lie ahead and proposes a framework for striking a balance between the benefits of allowing researchers to access medical information and the privacy concerns of individuals. In addition to contributing towards a sustainable model for secondary use of data in health research, the book also contributes significantly to research in this field and serves as an essential comparative reference for similar jurisdictions.Contributorsinclude Wendy Armstrong (Consumers' Association of Canada, Alberta), Penny Ballem (Consultant), David Henry (Institute for Clinical Evaluative Sciences), Alan Katz (Manitoba Centre for Health Policy), Pat Kosseim (Genome Canada), Shoo Lee (Mount Sinai Hospital, Toronto), Steven Lewis (Consultant), Lisa Lix (University of Saskatchewan), William Lowrance (Consultant), Pat Martens (Manitoba Centre for Health Policy), Dale McMurchy (Consultant), Andrew F. Nelson (Health Partners Research Foundation), Robert Ouellet (Canadian Medical Association), Dorothy Pringle (University of Toronto), Robert J. Reid (Group Health Centre for Health Studies), Valerie Steeves (University of Ottawa), Terry Sullivan (Cancer Care Ontario), Simon Sutcliffe (British Columbia Cancer Agency), Robyn Tamblyn (McGill University), Jack Tu (Institute for Clinical Evaluative Studies), Don Willison (McMaster University), Michael Wolfson (Statistics Canada), and Glenda Yeates (Canadian Institute for Health Information).

The latest book from best-selling author Victoria L. Bernhardt is an easy-to-read primer that describes what it takes to achieve student learning growth at every grade level, in every subject area, and with every student group. In this new edition, readers will learn how to use data to inform their continuous school improvement as they develop an appreciation of the various types of data, uses for data, and how data are involved in the process. This accessible, updated edition provides a wealth of straightforward and accessible strategies that will allow educators to become comfortable with the many uses of data in increasing student improvement. Data, Data Everywhere, 2nd edition, provides a framework and summary of the continuous school improvement framework. It is a perfect resource for teachers, administrators, support staff, and students of leadership to guide comprehensive school improvement that will make a difference for all students.

Our newly digital world is generating an almost unimaginable amount of data about all of us. Such a vast amount of data is useless without plans and strategies that are designed to cope with its size and complexity, and which enable organisations to leverage the information to create value. This book is a refreshingly practical, yet theoretically sound roadmap to leveraging big data and analytics. Creating Value with Big Data Analytics provides a nuanced view of big data development, arguing that big data in itself is not a revolution but an evolution of the increasing availability of data that has been observed in recent times. Building on the authors’ extensive academic and practical knowledge, this book aims to provide managers and analysts with strategic directions and practical analytical solutions on how to create value from existing and new big data. By tying data and analytics to specific goals and processes for implementation, this is a much-needed book that will be essential reading for students and specialists of data analytics, marketing research, and customer relationship management.

The Harvard Law Review is offered in a digital edition, featuring active Contents, linked notes, and proper ebook formatting. The contents of Issue 7 include a Symposium on privacy and several contributions from leading legal scholars: Article, "Agency Self-Insulation Under Presidential Review," by Jennifer Nou Commentary, "The Office of Information and Regulatory Affairs: Myths and Realities," by Cass R. Sunstein SYMPOSIUM: PRIVACY AND TECHNOLOGY "Introduction: Privacy Self-Management and the Consent Dilemma," by Daniel J. Solove "What Privacy Is For," by Julie E. Cohen "The Dangers of Surveillance," by Neil M. Richards "The EU-U.S. Privacy Collision: A Turn to Institutions and Procedures," by Paul M. Schwartz "Toward a Positive Theory of Privacy Law," by Lior Jacob Strahilevitz Book Review, "Does the Past Matter? On the Origins of Human Rights," by Philip Alston A student Note explores "Enabling Television Competition in a Converged Market." In addition, extensive student analyses of Recent Cases discuss such subjects as First Amendment implications of falsely wearing military uniforms, First Amendment implications of public employment job duties, justiciability of claims that Scientologists violated trafficking laws, habeas corpus law, and ineffective assistance of counsel claims. Finally, the issue includes several summaries of Recent Publications. The Harvard Law Review is a student-run organization whose primary purpose is to publish a journal of legal scholarship. The Review comes out monthly from November through June and has roughly 2000 pages per volume. The organization is formally independent of the Harvard Law School. Student editors make all editorial and organizational decisions. This issue of the Review is May 2013, the 7th issue of academic year 2012-2013 (Volume 126).

Covers mathematical and algorithmic foundations of data science: machine learning, high-dimensional geometry, and analysis of large networks.