Principles of Data Management and Presentation PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Principles of Data Management and Presentation PDF full book. Access full book title Principles of Data Management and Presentation by Dr. John P. Hoffmann. Download full books in PDF and EPUB format.
Author: Dr. John P. Hoffmann
Publisher: Univ of California Press
ISBN: 0520964322
Category : Social Science
Languages : en
Pages : 288
Get Book
Book Description
The world is saturated with data. We are regularly presented with data in words, tables, and graphics. Students from many academic fields are now expected to be educated about data in one form or another. Yet the typical sequence of courses—introductory statistics and research methods—does not provide sufficient information about how to focus in on a research question, how to access data and work with datasets, or how to present data to various audiences. Principles of Data Management and Presentation addresses this gap. Assuming only that students have some familiarity with basic statistics and research methods, it provides a comprehensive set of principles for understanding and using data as part of a research project, including: • how to narrow a research topic to a specific research question • how to access and organize data that are useful for answering a research question • how to use software such as Stata, SPSS, and SAS to manage data • how to present data so that they convey a clear and effective message A companion website includes material to enhance the learning experience—specifically statistical software code and the datasets used in the examples, in text format as well as Stata, SPSS, and SAS formats. Visit www.ucpress.edu/go/datamanagement, Downloads tab.
Author: Dr. John P. Hoffmann
Publisher: Univ of California Press
ISBN: 0520964322
Category : Social Science
Languages : en
Pages : 288
Get Book
Book Description
The world is saturated with data. We are regularly presented with data in words, tables, and graphics. Students from many academic fields are now expected to be educated about data in one form or another. Yet the typical sequence of courses—introductory statistics and research methods—does not provide sufficient information about how to focus in on a research question, how to access data and work with datasets, or how to present data to various audiences. Principles of Data Management and Presentation addresses this gap. Assuming only that students have some familiarity with basic statistics and research methods, it provides a comprehensive set of principles for understanding and using data as part of a research project, including: • how to narrow a research topic to a specific research question • how to access and organize data that are useful for answering a research question • how to use software such as Stata, SPSS, and SAS to manage data • how to present data so that they convey a clear and effective message A companion website includes material to enhance the learning experience—specifically statistical software code and the datasets used in the examples, in text format as well as Stata, SPSS, and SAS formats. Visit www.ucpress.edu/go/datamanagement, Downloads tab.
Author: John P. Hoffmann
Publisher: Univ of California Press
ISBN: 0520289943
Category : Social Science
Languages : en
Pages : 282
Get Book
Book Description
Why research? -- Developing research questions -- Data -- Principles of data management -- Finding and using secondary data -- Primary and administrative data -- Working with missing data -- Principles of data presentation -- Designing tables for data presentations -- Designing graphics for data presentations
Author: Wilfried Lemahieu
Publisher: Cambridge University Press
ISBN: 1107186129
Category : Computers
Languages : en
Pages : 817
Get Book
Book Description
Introductory, theory-practice balanced text teaching the fundamentals of databases to advanced undergraduates or graduate students in information systems or computer science.
Author: National Research Council
Publisher: National Academies Press
ISBN: 0309182190
Category : Science
Languages : en
Pages : 150
Get Book
Book Description
The report outlines key elements to consider in designing a program to create climate-quality data from satellites. It examines historical attempts to create climate data records, provides advice on steps for generating, re-analyzing, and storing satellite climate data, and discusses the importance of partnering between agencies, academia, and industry. NOAA will use this report-the first in a two-part study-to draft an implementation plan for climate data records.
Author: Allen Dreibelbis
Publisher: IBM Press
ISBN: 9780134857503
Category :
Languages : en
Pages : 656
Get Book
Book Description
The Only Complete Technical Primer for MDM Planners, Architects, and Implementers Companies moving toward flexible SOA architectures often face difficult information management and integration challenges. The master data they rely on is often stored and managed in ways that are redundant, inconsistent, inaccessible, non-standardized, and poorly governed. Using Master Data Management (MDM), organizations can regain control of their master data, improve corresponding business processes, and maximize its value in SOA environments. Enterprise Master Data Management provides an authoritative, vendor-independent MDM technical reference for practitioners: architects, technical analysts, consultants, solution designers, and senior IT decisionmakers. Written by the IBM® data management innovators who are pioneering MDM, this book systematically introduces MDM's key concepts and technical themes, explains its business case, and illuminates how it interrelates with and enables SOA. Drawing on their experience with cutting-edge projects, the authors introduce MDM patterns, blueprints, solutions, and best practices published nowhere else--everything you need to establish a consistent, manageable set of master data, and use it for competitive advantage. Coverage includes How MDM and SOA complement each other Using the MDM Reference Architecture to position and design MDM solutions within an enterprise Assessing the value and risks to master data and applying the right security controls Using PIM-MDM and CDI-MDM Solution Blueprints to address industry-specific information management challenges Explaining MDM patterns as enablers to accelerate consistent MDM deployments Incorporating MDM solutions into existing IT landscapes via MDM Integration Blueprints Leveraging master data as an enterprise asset--bringing people, processes, and technology together with MDM and data governance Best practices in MDM deployment, including data warehouse and SAP integration
Author: Keith Gordon
Publisher: BCS, The Chartered Institute
ISBN:
Category : Business & Economics
Languages : en
Pages : 284
Get Book
Book Description
Organisations increasingly view data as a valuable corporate asset and its effective management can be vital to an organisation's success. This professional reference guide covers all the key areas including database development, data quality and corporate data modelling. It is not based on a particular proprietary system; it is business focused, providing the knowledge and techniques required to successfully implement the data management function.
Author: Bas van Gils
Publisher: Van Haren
ISBN: 9401805520
Category : Education
Languages : en
Pages : 306
Get Book
Book Description
The overall objective of this book is to show that data management is an exciting and valuable capability that is worth time and effort. More specifically it aims to achieve the following goals: 1. To give a “gentle” introduction to the field of DM by explaining and illustrating its core concepts, based on a mix of theory, practical frameworks such as TOGAF, ArchiMate, and DMBOK, as well as results from real-world assignments. 2. To offer guidance on how to build an effective DM capability in an organization.This is illustrated by various use cases, linked to the previously mentioned theoretical exploration as well as the stories of practitioners in the field. The primary target groups are: busy professionals who “are actively involved with managing data”. The book is also aimed at (Bachelor’s/ Master’s) students with an interest in data management. The book is industry-agnostic and should be applicable in different industries such as government, finance, telecommunications etc. Typical roles for which this book is intended: data governance office/ council, data owners, data stewards, people involved with data governance (data governance board), enterprise architects, data architects, process managers, business analysts and IT analysts. The book is divided into three main parts: theory, practice, and closing remarks. Furthermore, the chapters are as short and to the point as possible and also make a clear distinction between the main text and the examples. If the reader is already familiar with the topic of a chapter, he/she can easily skip it and move on to the next.
Author: M. Tamer Özsu
Publisher: Springer Science & Business Media
ISBN: 1441988343
Category : Computers
Languages : en
Pages : 846
Get Book
Book Description
This third edition of a classic textbook can be used to teach at the senior undergraduate and graduate levels. The material concentrates on fundamental theories as well as techniques and algorithms. The advent of the Internet and the World Wide Web, and, more recently, the emergence of cloud computing and streaming data applications, has forced a renewal of interest in distributed and parallel data management, while, at the same time, requiring a rethinking of some of the traditional techniques. This book covers the breadth and depth of this re-emerging field. The coverage consists of two parts. The first part discusses the fundamental principles of distributed data management and includes distribution design, data integration, distributed query processing and optimization, distributed transaction management, and replication. The second part focuses on more advanced topics and includes discussion of parallel database systems, distributed object management, peer-to-peer data management, web data management, data stream systems, and cloud computing. New in this Edition: • New chapters, covering database replication, database integration, multidatabase query processing, peer-to-peer data management, and web data management. • Coverage of emerging topics such as data streams and cloud computing • Extensive revisions and updates based on years of class testing and feedback Ancillary teaching materials are available.
Author: Arthur D. Chapman
Publisher: GBIF
ISBN: 8792020038
Category : Biodiversity
Languages : en
Pages : 61
Get Book
Book Description
Author: Dama International
Publisher:
ISBN: 9781634622349
Category : Database management
Languages : en
Pages : 628
Get Book
Book Description
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.
