Dealing With Data
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Managing Research Data
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Author : Graham Pryor
language : en
Publisher: Facet Publishing
Release Date : 2012-01-20
Managing Research Data written by Graham Pryor and has been published by Facet Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-01-20 with Language Arts & Disciplines categories.
This title defines what is required to achieve a culture of effective data management offering advice on the skills required, legal and contractual obligations, strategies and management plans and the data management infrastructure of specialists and services. Data management has become an essential requirement for information professionals over the last decade, particularly for those supporting the higher education research community, as more and more digital information is created and stored. As budgets shrink and funders of research demand evidence of value for money and demonstrable benefits for society, there is increasing pressure to provide plans for the sustainable management of data. Ensuring that important data remains discoverable, accessible and intelligible and is shared as part of a larger web of knowledge will mean that research has a life beyond its initial purpose and can offer real utility to the wider community. This edited collection, bringing together leading figures in the field from the UK and around the world, provides an introduction to all the key data issues facing the HE and information management communities. Each chapter covers a critical element of data management: • Why manage research data? • The lifecycle of data management • Research data policies: principles, requirements and trends • Sustainable research data • Data management plans and planning • Roles and responsibilities – libraries, librarians and data • Research data management: opportunities and challenges for HEIs • The national data centres • Contrasting national research data strategies: Australia and the USA • Emerging infrastructure and services for research data management and curation in the UK and Europe Readership: This is essential reading for librarians and information professionals working in the higher education sector, the research community, policy makers and university managers. It will also be a useful introduction for students taking courses in information management, archivists and national library services.
Best Practices In Data Cleaning
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Author : Jason W. Osborne
language : en
Publisher: SAGE
Release Date : 2013
Best Practices In Data Cleaning written by Jason W. Osborne and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with Mathematics categories.
Many researchers jump straight from data collection to data analysis without realizing how analyses and hypothesis tests can go profoundly wrong without clean data. This book provides a clear, step-by-step process of examining and cleaning data in order to decrease error rates and increase both the power and replicability of results. Jason W. Osborne, author of Best Practices in Quantitative Methods (SAGE, 2008) provides easily-implemented suggestions that are research-based and will motivate change in practice by empirically demonstrating, for each topic, the benefits of following best practices and the potential consequences of not following these guidelines. If your goal is to do the best research you can do, draw conclusions that are most likely to be accurate representations of the population(s) you wish to speak about, and report results that are most likely to be replicated by other researchers, then this basic guidebook will be indispensible.
Managing Data Science
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Author : Kirill Dubovikov
language : en
Publisher:
Release Date : 2019-11-12
Managing Data Science written by Kirill Dubovikov and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-12 with categories.
Understand data science concepts and methodologies to manage and deliver top-notch solutions for your organization Key Features Learn the basics of data science and explore its possibilities and limitations Manage data science projects and assemble teams effectively even in the most challenging situations Understand management principles and approaches for data science projects to streamline the innovation process Book Description Data science and machine learning can transform any organization and unlock new opportunities. However, employing the right management strategies is crucial to guide the solution from prototype to production. Traditional approaches often fail as they don't entirely meet the conditions and requirements necessary for current data science projects. In this book, you'll explore the right approach to data science project management, along with useful tips and best practices to guide you along the way. After understanding the practical applications of data science and artificial intelligence, you'll see how to incorporate them into your solutions. Next, you will go through the data science project life cycle, explore the common pitfalls encountered at each step, and learn how to avoid them. Any data science project requires a skilled team, and this book will offer the right advice for hiring and growing a data science team for your organization. Later, you'll be shown how to efficiently manage and improve your data science projects through the use of DevOps and ModelOps. By the end of this book, you will be well versed with various data science solutions and have gained practical insights into tackling the different challenges that you'll encounter on a daily basis. What you will learn Understand the underlying problems of building a strong data science pipeline Explore the different tools for building and deploying data science solutions Hire, grow, and sustain a data science team Manage data science projects through all stages, from prototype to production Learn how to use ModelOps to improve your data science pipelines Get up to speed with the model testing techniques used in both development and production stages Who this book is for This book is for data scientists, analysts, and program managers who want to use data science for business productivity by incorporating data science workflows efficiently. Some understanding of basic data science concepts will be useful to get the most out of this book.
Managing Your Business Data
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Author : Theresa Kushner
language : en
Publisher: Racom Communication
Release Date : 2008-10
Managing Your Business Data written by Theresa Kushner and has been published by Racom Communication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-10 with Business & Economics categories.
As a businessperson, you probably have more data available than ever before. For many, more data just fuels the fire of their love/hate relationship with it. You love it when it gives you good information about how to compete more effectively. But, you hate it when you can't get sales figures in time. This book was written for those who want to understand the lifeblood of their company, who want to be able to make better decisions, and who know that managing information is the best way to protect and grow a business. This book is designed to help you think about the use of data and its impact on your daily operation. It provides practical guidance to balance the use of hard facts and professional instincts; how to identify and focus on the numbers that matter; how to meet risk and security standards; and how to grow a data culture and make it work for you.
Principles Of Statistical Data Handling
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Author : Fred Davidson
language : en
Publisher:
Release Date : 1996
Principles Of Statistical Data Handling written by Fred Davidson and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996 with Educational statistics categories.
This volume demonstrates how to input, manipulate and debug data to make substantive analysis easier and more accurate. Using a series of principles, universal concepts that apply no matter what the data-gathering context or computer software, Fred Davidson presents a situation or a problem, suggests how it might be resolved and demonstrates the implementation of each principle as it appears in the command languages of SAS and SPSS.
Managing Scientific Information And Research Data
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Author : Svetla Baykoucheva
language : en
Publisher: Chandos Publishing
Release Date : 2015-07-10
Managing Scientific Information And Research Data written by Svetla Baykoucheva and has been published by Chandos Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-07-10 with Business & Economics categories.
Innovative technologies are changing the way research is performed, preserved, and communicated. Managing Scientific Information and Research Data explores how these technologies are used and provides detailed analysis of the approaches and tools developed to manage scientific information and data. Following an introduction, the book is then divided into 15 chapters discussing the changes in scientific communication; new models of publishing and peer review; ethics in scientific communication; preservation of data; discovery tools; discipline-specific practices of researchers for gathering and using scientific information; academic social networks; bibliographic management tools; information literacy and the information needs of students and researchers; the involvement of academic libraries in eScience and the new opportunities it presents to librarians; and interviews with experts in scientific information and publishing.
Handling Qualitative Data
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Author : Lyn Richards
language : en
Publisher: SAGE
Release Date : 2014-11-30
Handling Qualitative Data written by Lyn Richards and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-30 with Social Science categories.
The Third Edition of Lyn Richards′ best-selling book is the perfect introduction to qualitative research for students and practitioners. Recognizing that for many new researchers dealing with data is the main point of departure, this book helps them to acquire an understanding of the skills and methodological issues that are central to qualitative research. Author Lyn Richards provides practical guidance on how to handle, reflect on and make sense of rich data, while at the same time showing how a consideration of methods and their philosophical underpinnings informs how we should best handle our data. Detailed sections cover: the processes of making, meeting, sorting, coding, documenting, and exploring qualitative data; how to see a study as a whole and write it, and making and justifying claims. Each chapter smoothly integrates software use with discussion of the main challenges that software users are likely to encounter. Novice researchers who use this book will be able to achieve valid and useful outcomes from qualitative analysis, and ensure they do justice to their data.
Handling Qualitative Data
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Author : Lyn Richards
language : en
Publisher: SAGE
Release Date : 2005-04-09
Handling Qualitative Data written by Lyn Richards and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-04-09 with Social Science categories.
Handling Qualitative Data introduces students and practitioners to qualitative research in a uniquely practical manner. Firstly, it recognizes that for many novice researchers, data, rather than methods and their philosophical underpinnings, are the point of departure. Secondly, it advocates a progressive accumulation of skills and understanding of methodological issues as they are needed. This enables the student to perform efficaciously from the start by immediately being in a position to handle, reflect upon and get results from, small amounts of data, giving them a launch pad to more complex endeavours.
Managing Data Science
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Author : Kirill Dubovikov
language : en
Publisher: Packt Publishing Ltd
Release Date : 2019-11-12
Managing Data Science written by Kirill Dubovikov and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-12 with Computers categories.
Understand data science concepts and methodologies to manage and deliver top-notch solutions for your organization Key FeaturesLearn the basics of data science and explore its possibilities and limitationsManage data science projects and assemble teams effectively even in the most challenging situationsUnderstand management principles and approaches for data science projects to streamline the innovation processBook Description Data science and machine learning can transform any organization and unlock new opportunities. However, employing the right management strategies is crucial to guide the solution from prototype to production. Traditional approaches often fail as they don't entirely meet the conditions and requirements necessary for current data science projects. In this book, you'll explore the right approach to data science project management, along with useful tips and best practices to guide you along the way. After understanding the practical applications of data science and artificial intelligence, you'll see how to incorporate them into your solutions. Next, you will go through the data science project life cycle, explore the common pitfalls encountered at each step, and learn how to avoid them. Any data science project requires a skilled team, and this book will offer the right advice for hiring and growing a data science team for your organization. Later, you'll be shown how to efficiently manage and improve your data science projects through the use of DevOps and ModelOps. By the end of this book, you will be well versed with various data science solutions and have gained practical insights into tackling the different challenges that you'll encounter on a daily basis. What you will learnUnderstand the underlying problems of building a strong data science pipelineExplore the different tools for building and deploying data science solutionsHire, grow, and sustain a data science teamManage data science projects through all stages, from prototype to productionLearn how to use ModelOps to improve your data science pipelinesGet up to speed with the model testing techniques used in both development and production stagesWho this book is for This book is for data scientists, analysts, and program managers who want to use data science for business productivity by incorporating data science workflows efficiently. Some understanding of basic data science concepts will be useful to get the most out of this book.
Managing Data Quality
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Author : Tim King
language : en
Publisher: BCS, The Chartered Institute for IT
Release Date : 2020-04-27
Managing Data Quality written by Tim King and has been published by BCS, The Chartered Institute for IT this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-27 with categories.
This book explains data quality management in practical terms, focusing on three key areas - the nature of data in enterprises, the purpose and scope of data quality management, and implementing a data quality management system, in line with ISO 8000-61. Examples of good practice in data quality management are also included.