Data Management And Analysis

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Text Data Management and Analysis

ChengXiang Zhai,Sean Massung
Text Data Management and Analysis Book PDF

Author : ChengXiang Zhai,Sean Massung
Publisher : Morgan & Claypool
Page : 530 pages
File Size : 55,6 Mb
Release : 2016-06-30
Category : Computers
ISBN : 9781970001181

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Text Data Management and Analysis by ChengXiang Zhai,Sean Massung Pdf

Recent years have seen a dramatic growth of natural language text data, including web pages, news articles, scientific literature, emails, enterprise documents, and social media such as blog articles, forum posts, product reviews, and tweets. This has led to an increasing demand for powerful software tools to help people analyze and manage vast amounts of text data effectively and efficiently. Unlike data generated by a computer system or sensors, text data are usually generated directly by humans, and are accompanied by semantically rich content. As such, text data are especially valuable for discovering knowledge about human opinions and preferences, in addition to many other kinds of knowledge that we encode in text. In contrast to structured data, which conform to well-defined schemas (thus are relatively easy for computers to handle), text has less explicit structure, requiring computer processing toward understanding of the content encoded in text. The current technology of natural language processing has not yet reached a point to enable a computer to precisely understand natural language text, but a wide range of statistical and heuristic approaches to analysis and management of text data have been developed over the past few decades. They are usually very robust and can be applied to analyze and manage text data in any natural language, and about any topic. This book provides a systematic introduction to all these approaches, with an emphasis on covering the most useful knowledge and skills required to build a variety of practically useful text information systems. The focus is on text mining applications that can help users analyze patterns in text data to extract and reveal useful knowledge. Information retrieval systems, including search engines and recommender systems, are also covered as supporting technology for text mining applications. The book covers the major concepts, techniques, and ideas in text data mining and information retrieval from a practical viewpoint, and includes many hands-on exercises designed with a companion software toolkit (i.e., MeTA) to help readers learn how to apply techniques of text mining and information retrieval to real-world text data and how to experiment with and improve some of the algorithms for interesting application tasks. The book can be used as a textbook for a computer science undergraduate course or a reference book for practitioners working on relevant problems in analyzing and managing text data.

Highlighting the Importance of Big Data Management and Analysis for Various Applications

Mohammad Moshirpour,Behrouz Far,Reda Alhajj
Highlighting the Importance of Big Data Management and Analysis for Various Applications Book PDF

Author : Mohammad Moshirpour,Behrouz Far,Reda Alhajj
Publisher : Springer
Page : 168 pages
File Size : 50,8 Mb
Release : 2017-08-22
Category : Business & Economics
ISBN : 9783319602554

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Highlighting the Importance of Big Data Management and Analysis for Various Applications by Mohammad Moshirpour,Behrouz Far,Reda Alhajj Pdf

This book addresses the impacts of various types of services such as infrastructure, platforms, software, and business processes that cloud computing and Big Data have introduced into business. Featuring chapters which discuss effective and efficient approaches in dealing with the inherent complexity and increasing demands in data science, a variety of application domains are covered. Various case studies by data management and analysis experts are presented in these chapters. Covered applications include banking, social networks, bioinformatics, healthcare, transportation and criminology. Highlighting the Importance of Big Data Management and Analysis for Various Applications will provide the reader with an understanding of how data management and analysis are adapted to these applications. This book will appeal to researchers and professionals in the field.

Using R and RStudio for Data Management, Statistical Analysis, and Graphics

Nicholas J. Horton,Ken Kleinman
Using R and RStudio for Data Management Statistical Analysis and Graphics Book PDF

Author : Nicholas J. Horton,Ken Kleinman
Publisher : CRC Press
Page : 313 pages
File Size : 43,6 Mb
Release : 2015-03-10
Category : Mathematics
ISBN : 9781482237375

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Using R and RStudio for Data Management, Statistical Analysis, and Graphics by Nicholas J. Horton,Ken Kleinman Pdf

Improve Your Analytical SkillsIncorporating the latest R packages as well as new case studies and applications, Using R and RStudio for Data Management, Statistical Analysis, and Graphics, Second Edition covers the aspects of R most often used by statistical analysts. New users of R will find the book's simple approach easy to understand while more

SAS and R

Ken Kleinman,Nicholas J. Horton
SAS and R Book PDF

Author : Ken Kleinman,Nicholas J. Horton
Publisher : CRC Press
Page : 473 pages
File Size : 41,6 Mb
Release : 2014-07-17
Category : Mathematics
ISBN : 9781466584495

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SAS and R by Ken Kleinman,Nicholas J. Horton Pdf

An Up-to-Date, All-in-One Resource for Using SAS and R to Perform Frequent Tasks The first edition of this popular guide provided a path between SAS and R using an easy-to-understand, dictionary-like approach. Retaining the same accessible format, SAS and R: Data Management, Statistical Analysis, and Graphics, Second Edition explains how to easily perform an analytical task in both SAS and R, without having to navigate through the extensive, idiosyncratic, and sometimes unwieldy software documentation. The book covers many common tasks, such as data management, descriptive summaries, inferential procedures, regression analysis, and graphics, along with more complex applications. New to the Second Edition This edition now covers RStudio, a powerful and easy-to-use interface for R. It incorporates a number of additional topics, including using application program interfaces (APIs), accessing data through database management systems, using reproducible analysis tools, and statistical analysis with Markov chain Monte Carlo (MCMC) methods and finite mixture models. It also includes extended examples of simulations and many new examples. Enables Easy Mobility between the Two Systems Through the extensive indexing and cross-referencing, users can directly find and implement the material they need. SAS users can look up tasks in the SAS index and then find the associated R code while R users can benefit from the R index in a similar manner. Numerous example analyses demonstrate the code in action and facilitate further exploration. The datasets and code are available for download on the book’s website.

Crop Variety Trials

Weikai Yan
Crop Variety Trials Book PDF

Author : Weikai Yan
Publisher : John Wiley & Sons
Page : 360 pages
File Size : 46,7 Mb
Release : 2014-03-11
Category : Technology & Engineering
ISBN : 9781118688564

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Crop Variety Trials by Weikai Yan Pdf

Variety trials are an essential step in crop breeding and production. These trials are a significant investment in time and resources and inform numerous decisions from cultivar development to end-use. Crop Variety Trials: Methods and Analysis is a practical volume that provides valuable theoretical foundations as well as a guide to step-by-step implementation of effective trial methods and analysis in determining the best varieties and cultivars. Crop Variety Trials is divided into two sections. The first section provides the reader with a sound theoretical framework of variety evaluation and trial analysis. Chapters provide insights into the theories of quantitative genetics and principles of analyzing data. The second section of the book gives the reader with a practical step-by-step guide to accurately analyzing crop variety trial data. Combined these sections provide the reader with fuller understanding of the nature of variety trials, their objectives, and user-friendly database and statistical tools that will enable them to produce accurate analysis of data.

Data Management for Researchers

Kristin Briney
Data Management for Researchers Book PDF

Author : Kristin Briney
Publisher : Pelagic Publishing Ltd
Page : 312 pages
File Size : 45,7 Mb
Release : 2015-09-01
Category : Computers
ISBN : 9781784270131

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Data Management for Researchers by Kristin Briney Pdf

A comprehensive guide to everything scientists need to know about data management, this book is essential for researchers who need to learn how to organize, document and take care of their own data. Researchers in all disciplines are faced with the challenge of managing the growing amounts of digital data that are the foundation of their research. Kristin Briney offers practical advice and clearly explains policies and principles, in an accessible and in-depth text that will allow researchers to understand and achieve the goal of better research data management. Data Management for Researchers includes sections on: * The data problem – an introduction to the growing importance and challenges of using digital data in research. Covers both the inherent problems with managing digital information, as well as how the research landscape is changing to give more value to research datasets and code. * The data lifecycle – a framework for data’s place within the research process and how data’s role is changing. Greater emphasis on data sharing and data reuse will not only change the way we conduct research but also how we manage research data. * Planning for data management – covers the many aspects of data management and how to put them together in a data management plan. This section also includes sample data management plans. * Documenting your data – an often overlooked part of the data management process, but one that is critical to good management; data without documentation are frequently unusable. * Organizing your data – explains how to keep your data in order using organizational systems and file naming conventions. This section also covers using a database to organize and analyze content. * Improving data analysis – covers managing information through the analysis process. This section starts by comparing the management of raw and analyzed data and then describes ways to make analysis easier, such as spreadsheet best practices. It also examines practices for research code, including version control systems. * Managing secure and private data – many researchers are dealing with data that require extra security. This section outlines what data falls into this category and some of the policies that apply, before addressing the best practices for keeping data secure. * Short-term storage – deals with the practical matters of storage and backup and covers the many options available. This section also goes through the best practices to insure that data are not lost. * Preserving and archiving your data – digital data can have a long life if properly cared for. This section covers managing data in the long term including choosing good file formats and media, as well as determining who will manage the data after the end of the project. * Sharing/publishing your data – addresses how to make data sharing across research groups easier, as well as how and why to publicly share data. This section covers intellectual property and licenses for datasets, before ending with the altmetrics that measure the impact of publicly shared data. * Reusing data – as more data are shared, it becomes possible to use outside data in your research. This chapter discusses strategies for finding datasets and lays out how to cite data once you have found it. This book is designed for active scientific researchers but it is useful for anyone who wants to get more from their data: academics, educators, professionals or anyone who teaches data management, sharing and preservation. "An excellent practical treatise on the art and practice of data management, this book is essential to any researcher, regardless of subject or discipline." —Robert Buntrock, Chemical Information Bulletin

SAS and R

Ken Kleinman,Nicholas J. Horton
SAS and R Book PDF

Author : Ken Kleinman,Nicholas J. Horton
Publisher : CRC Press
Page : 325 pages
File Size : 51,5 Mb
Release : 2009-07-21
Category : Mathematics
ISBN : 9781420070590

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SAS and R by Ken Kleinman,Nicholas J. Horton Pdf

An All-in-One Resource for Using SAS and R to Carry out Common TasksProvides a path between languages that is easier than reading complete documentationSAS and R: Data Management, Statistical Analysis, and Graphics presents an easy way to learn how to perform an analytical task in both SAS and R, without having to navigate through the extensive, id

Data Management and Data Description

Richard Williams
Data Management and Data Description Book PDF

Author : Richard Williams
Publisher : Routledge
Page : 360 pages
File Size : 40,5 Mb
Release : 2019-01-15
Category : Social Science
ISBN : 9780429873317

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Data Management and Data Description by Richard Williams Pdf

Published in 1992. The author sets out the main issues in Data Management, from the first principles of meta modelling and data description through the comprehensive management exploitation, re-use, valuation, extension and enhancement of data as a valuable organizational resource. Using his recent in-depth experience of a major trans-European project, he highlights data value metrics and provides examples of extended data analysis to assist readers to produce corporate data architectures. The book considers how the techniques of data management can be applied in the wider community of business, institutional and organizational settings and considers how new types of data (from the EDIFACT world) can be integrated into the existing data management environments of large data processing functions. This wide-ranging text considers existing work in the field of data resource management and extends the concepts of data resource valuation. References are made to new aspects of metrics for data value and how they can be applied. It will interest strategic business planners, information systems, and DP managers and executives, data-management personnel and data analysts, and academics involved in MSc and BSc courses on Dara Analysis, CASE repositories and structured methods.

Big Data Management

Fausto Pedro García Márquez,Benjamin Lev
Big Data Management Book PDF

Author : Fausto Pedro García Márquez,Benjamin Lev
Publisher : Springer
Page : 267 pages
File Size : 49,8 Mb
Release : 2016-11-15
Category : Computers
ISBN : 9783319454986

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Big Data Management by Fausto Pedro García Márquez,Benjamin Lev Pdf

This book focuses on the analytic principles of business practice and big data. Specifically, it provides an interface between the main disciplines of engineering/technology and the organizational and administrative aspects of management, serving as a complement to books in other disciplines such as economics, finance, marketing and risk analysis. The contributors present their areas of expertise, together with essential case studies that illustrate the successful application of engineering management theories in real-life examples.

Data Management and Analysis Using JMP

Jane E Oppenlander,Patricia Schaffer
Data Management and Analysis Using JMP Book PDF

Author : Jane E Oppenlander,Patricia Schaffer
Publisher : SAS Institute
Page : 250 pages
File Size : 50,6 Mb
Release : 2017-10-17
Category : Computers
ISBN : 9781629605401

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Data Management and Analysis Using JMP by Jane E Oppenlander,Patricia Schaffer Pdf

A holistic, step-by-step approach to analyzing health care data! Written for both beginner and intermediate JMP users working in or studying health care, Data Management and Analysis Using JMP: Health Care Case Studies bridges the gap between taking traditional statistics courses and successfully applying statistical analysis in the workplace. Authors Jane Oppenlander and Patricia Schaffer begin by illustrating techniques to prepare data for analysis, followed by presenting effective methods to summarize, visualize, and analyze data. The statistical analysis methods covered in the book are the foundational techniques commonly applied to meet regulatory, operational, budgeting, and research needs in the health care field. This example-driven book shows practitioners how to solve real-world problems by using an approach that includes problem definition, data management, selecting the appropriate analysis methods, step-by-step JMP instructions, and interpreting statistical results in context. Practical strategies for selecting appropriate statistical methods, remediating data anomalies, and interpreting statistical results in the domain context are emphasized. The cases presented in Data Management and Analysis Using JMP use multiple statistical methods. A progression of methods--from univariate to multivariate--is employed, illustrating a logical approach to problem-solving. Much of the data used in these cases is open source and drawn from a variety of health care settings. The book offers a welcome guide to working professionals as well as students studying statistics in health care-related fields.

Telling Your Data Story

Scott Taylor
Telling Your Data Story Book PDF

Author : Scott Taylor
Publisher : Unknown
Page : 196 pages
File Size : 47,9 Mb
Release : 2020-11-15
Category : Business & Economics
ISBN : 1634628950

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Telling Your Data Story by Scott Taylor Pdf

The Data Whisperer's practical guide to explaining and understanding the strategic value of data management. The need for data management is everywhere across your company. The value of every digitally transformative customer-facing initiative, every data science and analytics-based project, every as-a-service offering, every foray into e-commerce, and every enterprise software implementation is inextricably linked to the successful output of data management efforts. Although it is a simple function of garbage in garbage out, that slogan rarely drives any sustainable executive action. We need to tell a better data story. Data Storytelling is probably the hottest non-technical trend in the technology-related space. But it does not directly support data management because it is focused on analytics or telling stories with data. So, it is time to expand the realm of Data Storytelling to recognize the role of data management by telling stories about data. Learn how to secure stakeholder involvement and executive commitment to fund and support data management as a systematic, consistent, fundamental part of your business. This book is for: Data management leaders trying to explain your value to C-Level and business stakeholders. As a practitioner, you may already know how to fix your data, but your business leaders ignore your advice. When you explain data management to the business, they may nod "yes" on the outside, but they nod off on the inside. Business stakeholders trying to comprehend why data management is important. Many business people may be frightened, threatened, intimidated, or at the very least confused and bewildered by the techno-babble often associated with data-related conversations. If you want to know more about why data management needs to be a strategic imperative in your organization, you'll learn it here in simple terms. Data scientists looking to understand better how you connect to "The Business." A recurring struggle I hear from data scientists is the need to get "closer to business." If you are a data scientist, then you need to understand your company's data story. The more you can align your work to the core value your company delivers, the more successful you will be. This book will help you discover the essence of why data brings value to your business. Anyone interested in understanding the business value of data management. I offer simple explanations about why data management is essential for your organization. Without going deep into technical concepts and processes, I focus on the business-related outputs. I share ways you can think about what foundational data does. Its importance is vital for the future of your enterprise. Since this is a book about telling data stories, I share it through stories divided into five sections: My data story. Why I know what I know and why you should listen to me. Everyone's data story. A collection of classic, foundational data situations relevant to all enterprises. Framing your data story. A set of simple frameworks about data value. Selling your data story. Tips on creating a compelling narrative. Building your data story. Why you must align with the strategic intentions of your enterprise.

Data Management on New Hardware

Spyros Blanas,Rajesh Bordawekar,Tirthankar Lahiri,Justin Levandoski,Andrew Pavlo
Data Management on New Hardware Book PDF

Author : Spyros Blanas,Rajesh Bordawekar,Tirthankar Lahiri,Justin Levandoski,Andrew Pavlo
Publisher : Springer
Page : 167 pages
File Size : 55,7 Mb
Release : 2017-03-21
Category : Computers
ISBN : 9783319561110

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Data Management on New Hardware by Spyros Blanas,Rajesh Bordawekar,Tirthankar Lahiri,Justin Levandoski,Andrew Pavlo Pdf

This book contains selected papers from the 7th International Workshop on Accelerating Analytics and Data Management Systems Using Modern Processor and Storage Architectures, ADMS 2016, and the 4th International Workshop on In-Memory Data Management and Analytics, IMDM 2016, held in New Dehli, India, in September 2016. The joint Workshops were co-located with VLDB 2016. The 9 papers presented were carefully reviewed and selected from 18 submissions. They investigate opportunities in accelerating analytics/data management systems and workloads (including traditional OLTP, data warehousing/OLAP, ETL streaming/real-time, business analytics, and XML/RDF processing) running memory-only environments, using processors (e.g. commodity and specialized multi-core, GPUs and FPGAs, storage systems (e.g. storage-class memories like SSDs and phase-change memory), and hybrid programming models like CUDA, OpenCL, and Open ACC. The papers also explore the interplay between overall system design, core algorithms, query optimization strategies, programming approaches, performance modeling and evaluation, from the perspective of data management applications.

Effective Big Data Management and Opportunities for Implementation

Singh, Manoj Kumar,G., Dileep Kumar
Effective Big Data Management and Opportunities for Implementation Book PDF

Author : Singh, Manoj Kumar,G., Dileep Kumar
Publisher : IGI Global
Page : 324 pages
File Size : 44,5 Mb
Release : 2016-06-20
Category : Computers
ISBN : 9781522501831

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Effective Big Data Management and Opportunities for Implementation by Singh, Manoj Kumar,G., Dileep Kumar Pdf

“Big data” has become a commonly used term to describe large-scale and complex data sets which are difficult to manage and analyze using standard data management methodologies. With applications across sectors and fields of study, the implementation and possible uses of big data are limitless. Effective Big Data Management and Opportunities for Implementation explores emerging research on the ever-growing field of big data and facilitates further knowledge development on methods for handling and interpreting large data sets. Providing multi-disciplinary perspectives fueled by international research, this publication is designed for use by data analysts, IT professionals, researchers, and graduate-level students interested in learning about the latest trends and concepts in big data.

Managing Projects with Make

Andrew Oram,Steve Talbott
Managing Projects with Make Book PDF

Author : Andrew Oram,Steve Talbott
Publisher : "O'Reilly Media, Inc."
Page : 170 pages
File Size : 54,5 Mb
Release : 1991
Category : Business & Economics
ISBN : 0937175900

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Managing Projects with Make by Andrew Oram,Steve Talbott Pdf

Software -- Operating Systems.

DAMA-DMBOK

Dama International
DAMA DMBOK Book PDF

Author : Dama International
Publisher : Unknown
Page : 628 pages
File Size : 42,8 Mb
Release : 2017
Category : Database management
ISBN : 1634622340

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DAMA-DMBOK by Dama International Pdf

Defining a set of guiding principles for data management and describing how these principles can be applied within data management functional areas; Providing a functional framework for the implementation of enterprise data management practices; including widely adopted practices, methods and techniques, functions, roles, deliverables and metrics; Establishing a common vocabulary for data management concepts and serving as the basis for best practices for data management professionals. DAMA-DMBOK2 provides data management and IT professionals, executives, knowledge workers, educators, and researchers with a framework to manage their data and mature their information infrastructure, based on these principles: Data is an asset with unique properties; The value of data can be and should be expressed in economic terms; Managing data means managing the quality of data; It takes metadata to manage data; It takes planning to manage data; Data management is cross-functional and requires a range of skills and expertise; Data management requires an enterprise perspective; Data management must account for a range of perspectives; Data management is data lifecycle management; Different types of data have different lifecycle requirements; Managing data includes managing risks associated with data; Data management requirements must drive information technology decisions; Effective data management requires leadership commitment.