Data print books and ebooks | Elsevier

Executing Data Quality Projects

2nd Edition
May 21, 2021
Danette McGilvray
English
Paperback
9 7 8 0 1 2 8 1 8 0 1 5 0
eBook
9 7 8 0 1 2 8 1 8 0 1 6 7

Executing Data Quality Projects, Second Edition presents a structured yet flexible approach for creating, improving, sustaining and managing the quality of data and information within any organization. Studies show that data quality problems are costing businesses billions of dollars each year, with poor data linked to waste and inefficiency, damaged credibility among customers and suppliers, and an organizational inability to make sound decisions. Help is here! This book describes a proven Ten Step approach that combines a conceptual framework for understanding information quality with techniques, tools, and instructions for practically putting the approach to work – with the end result of high-quality trusted data and information, so critical to today’s data-dependent organizations. The Ten Steps approach applies to all types of data and all types of organizations – for-profit in any industry, non-profit, government, education, healthcare, science, research, and medicine. This book includes numerous templates, detailed examples, and practical advice for executing every step. At the same time, readers are advised on how to select relevant steps and apply them in different ways to best address the many situations they will face. The layout allows for quick reference with an easy-to-use format highlighting key concepts and definitions, important checkpoints, communication activities, best practices, and warnings. The experience of actual clients and users of the Ten Steps provide real examples of outputs for the steps plus highlighted, sidebar case studies called Ten Steps in Action. This book uses projects as the vehicle for data quality work and the word broadly to include: 1) focused data quality improvement projects, such as improving data used in supply chain management, 2) data quality activities in other projects such as building new applications and migrating data from legacy systems, integrating data because of mergers and acquisitions, or untangling data due to organizational breakups, and 3) ad hoc use of data quality steps, techniques, or activities in the course of daily work. The Ten Steps approach can also be used to enrich an organization’s standard SDLC (whether sequential or Agile) and it complements general improvement methodologies such as six sigma or lean. No two data quality projects are the same but the flexible nature of the Ten Steps means the methodology can be applied to all. The new Second Edition highlights topics such as artificial intelligence and machine learning, Internet of Things, security and privacy, analytics, legal and regulatory requirements, data science, big data, data lakes, and cloud computing, among others, to show their dependence on data and information and why data quality is more relevant and critical now than ever before.

Intelligent Data Security Solutions for e-Health Applications

1st Edition
August 26, 2020
Amit Kumar Singh + 1 more
English
Paperback
9 7 8 0 1 2 8 1 9 5 1 1 6
eBook
9 7 8 0 1 2 8 1 9 5 3 8 3

E-health applications such as tele-medicine, tele-radiology, tele-ophthalmology, and tele-diagnosis are very promising and have immense potential to improve global healthcare. They can improve access, equity, and quality through the connection of healthcare facilities and healthcare professionals, diminishing geographical and physical barriers. One critical issue, however, is related to the security of data transmission and access to the technologies of medical information. Currently, medical-related identity theft costs billions of dollars each year and altered medical information can put a person’s health at risk through misdiagnosis, delayed treatment or incorrect prescriptions. Yet, the use of hand-held devices for storing, accessing, and transmitting medical information is outpacing the privacy and security protections on those devices. Researchers are starting to develop some imperceptible marks to ensure the tamper-proofing, cost effective, and guaranteed originality of the medical records. However, the robustness, security and efficient image archiving and retrieval of medical data information against these cyberattacks is a challenging area for researchers in the field of e-health applications. Intelligent Data Security Solutions for e-Health Applications focuses on cutting-edge academic and industry-related research in this field, with particular emphasis on interdisciplinary approaches and novel techniques to provide security solutions for smart applications. The book provides an overview of cutting-edge security techniques and ideas to help graduate students, researchers, as well as IT professionals who want to understand the opportunities and challenges of using emerging techniques and algorithms for designing and developing more secure systems and methods for e-health applications.

Digital Media Steganography

1st Edition
June 27, 2020
Mahmoud Hassaballah
English
Paperback
9 7 8 0 1 2 8 1 9 4 3 8 6
eBook
9 7 8 0 1 2 8 1 9 4 3 9 3

The common use of the Internet and cloud services in transmission of large amounts of data over open networks and insecure channels, exposes that private and secret data to serious situations. Ensuring the information transmission over the Internet is safe and secure has become crucial, consequently information security has become one of the most important issues of human communities because of increased data transmission over social networks. Digital Media Steganography: Principles, Algorithms, and Advances covers fundamental theories and algorithms for practical design, while providing a comprehensive overview of the most advanced methodologies and modern techniques in the field of steganography. The topics covered present a collection of high-quality research works written in a simple manner by world-renowned leaders in the field dealing with specific research problems. It presents the state-of-the-art as well as the most recent trends in digital media steganography.

Essential Surgery

6th Edition
December 21, 2019
Philip J. Deakin + 3 more
English

Essential Surgery is well-established as one of the leading textbooks of surgery for medical students, core surgical trainees and those in professions allied to medicine. Covering general surgery, trauma, orthopaedics, vascular surgery, urology, paediatric surgery, cardiothoracic surgery, neurosurgery, maxillofacial surgery and ENT, it also incorporates appropriate levels of basic science throughout. The book is ideal to accompany clinical courses, as well as being a practical manual for readers at more advanced levels requiring a revision aid for exams. Its main aim is to stimulate the reader to a greater enjoyment and understanding of the practice of surgery.

Building Big Data Applications

1st Edition
November 15, 2019
Krish Krishnan
English
Paperback
9 7 8 0 1 2 8 1 5 7 4 6 6
eBook
9 7 8 0 1 2 8 1 5 8 0 4 3

Building Big Data Applications helps data managers and their organizations make the most of unstructured data with an existing data warehouse. It provides readers with what they need to know to make sense of how Big Data fits into the world of Data Warehousing. Readers will learn about infrastructure options and integration and come away with a solid understanding on how to leverage various architectures for integration. The book includes a wide range of use cases that will help data managers visualize reference architectures in the context of specific industries (healthcare, big oil, transportation, software, etc.).

The Master Adaptive Learner

1st Edition
September 29, 2019
William Cutrer + 4 more
English

Tomorrow’s best physicians will be those who continually learn, adjust, and innovate as new information and best practices evolve, reflecting adaptive expertise in response to practice challenges. As the first volume in the American Medical Association’s MedEd Innovation Series, The Master Adaptive Learner is an instructor-focused guide covering models for how to train and teach future clinicians who need to develop these adaptive skills and utilize them throughout their careers.

The Master Adaptive Learner

1st Edition
September 29, 2019
William Cutrer + 4 more
English

Tomorrow’s best physicians will be those who continually learn, adjust, and innovate as new information and best practices evolve, reflecting adaptive expertise in response to practice challenges. As the first volume in the American Medical Association’s MedEd Innovation Series, The Master Adaptive Learner is an instructor-focused guide covering models for how to train and teach future clinicians who need to develop these adaptive skills and utilize them throughout their careers.

The Master Adaptive Learner

1st Edition
September 29, 2019
William Cutrer + 4 more
English

Tomorrow’s best physicians will be those who continually learn, adjust, and innovate as new information and best practices evolve, reflecting adaptive expertise in response to practice challenges. As the first volume in the American Medical Association’s MedEd Innovation Series, The Master Adaptive Learner is an instructor-focused guide covering models for how to train and teach future clinicians who need to develop these adaptive skills and utilize them throughout their careers.

The Master Adaptive Learner

1st Edition
September 29, 2019
William Cutrer + 4 more
English

Tomorrow’s best physicians will be those who continually learn, adjust, and innovate as new information and best practices evolve, reflecting adaptive expertise in response to practice challenges. As the first volume in the American Medical Association’s MedEd Innovation Series, The Master Adaptive Learner is an instructor-focused guide covering models for how to train and teach future clinicians who need to develop these adaptive skills and utilize them throughout their careers.

Model Management and Analytics for Large Scale Systems

1st Edition
September 14, 2019
Bedir Tekinerdogan + 4 more
English
Paperback
9 7 8 0 1 2 8 1 6 6 4 9 9
eBook
9 7 8 0 1 2 8 1 6 6 5 0 5

Model Management and Analytics for Large Scale Systems covers the use of models and related artefacts (such as metamodels and model transformations) as central elements for tackling the complexity of building systems and managing data. With their increased use across diverse settings, the complexity, size, multiplicity and variety of those artefacts has increased. Originally developed for software engineering, these approaches can now be used to simplify the analytics of large-scale models and automate complex data analysis processes. Those in the field of data science will gain novel insights on the topic of model analytics that go beyond both model-based development and data analytics. This book is aimed at both researchers and practitioners who are interested in model-based development and the analytics of large-scale models, ranging from big data management and analytics, to enterprise domains. The book could also be used in graduate courses on model development, data analytics and data management.

Life Sciences

Physical Sciences & Engineering

Social Sciences & Humanities

Health

Books in Data

Executing Data Quality Projects

Intelligent Data Security Solutions for e-Health Applications

Digital Media Steganography

Essential Surgery

Building Big Data Applications

The Master Adaptive Learner

The Master Adaptive Learner

The Master Adaptive Learner

The Master Adaptive Learner

Model Management and Analytics for Large Scale Systems

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