| Contents |
Intro -- Title page -- Contents -- Preface -- 1 What is data science? -- Data, information, knowledge, wisdom -- Data everywhere -- The data deserts -- Data science -- The potential of data science -- From research data services to data science in libraries -- Programming in libraries -- Programming in this book -- The structure of this book -- 2 Little data, big data -- Big data -- Data formats -- Standalone files -- Application programming interfaces -- Unstructured data -- Data sources -- Data licences -- 3 The process of data science -- Modelling the data science process |
| Contents |
Frame the problem -- Collect data -- Transform and clean data -- Analyse data -- Visualise and communicate data -- Frame a new problem -- 4 Tools for data analysis -- Finding tools -- Software for data science -- Programming for data science -- 5 Clustering and social network analysis -- Network graphs -- Graph terminology -- Network matrix -- Visualisation -- Network analysis -- 6 Predictions and forecasts -- Predictions and forecasts beyond data science -- Predictions in a world of (limited) data -- Predicting and forecasting for information professionals -- Statistical methodologies |
| Contents |
7 Text analysis and mining -- Text analysis and mining, and information professionals -- Natural language processing -- Keywords and n-grams -- 8 The future of data science and information professionals -- Eight challenges to data science -- Ten steps to data science librarianship -- The final word: play -- References -- Appendix -- Programming concepts for data science -- Variables, data types and other classes -- Import libraries -- Functions and methods -- Loops and conditionals -- Final words of advice -- Further reading -- Index |
| Abstract |
<P>The growing importance of data science, and the increasing role of information professionals in the management and use of data, are brought together in <i>Practical Data Science for Information Professionals</i> to provide a practical introduction specifically designed for information professionals.</p><p>Data science has a wide range of applications within the information profession, from working alongside researchers in the discovery of new knowledge, to the application of business analytics for the smoother running of a library or library services. <i>Practical Data Science for Information Professionals</i> provides an accessible introduction to data science, using detailed examples and analysis on real data sets to explore the basics of the subject.</p><p>Content covered includes:</p><p><u><li>the growing importance of data science</li><li>the role of the information professional in data science</li><li>some of the most important tools and methods that information professionals may use</li><li>an analysis of the future of data science and the role of the information professional.</li></ul></p><p>This book will be of interest to all types of libraries around the world, from large academic libraries to small research libraries. By focusing on the application of open source software, the book aims to reduce barriers for readers to use the lessons learned within.</p> |
| General note | Title from publisher's bibliographic system (viewed on 14 Aug 2020). |
| Issued in other form | Print version: 9781783303441 |
| Genre/form | Electronic books. |
| ISBN | 1783303468 |
| ISBN | 9781783303465 (electronic bk.) |
| ISBN | (hardback) |
