000			04141nam a22003137a 4500
001			9231
003			BD-DhEWU
005			20221024155638.0
008			221024s2020 enka g b 001 0 eng d
020			_a9781783303441
020			_a9781783303458
040			_aBD-DhEWU _beng _cBD-DhEWU
041			_aeng
082			_2025 _aSTP 2020
100	1		_aStuart, David.
245	1	0	_aPractical data science for information professionals / _cDavid Stuart.
260			_aLondon : _bFacet Publishing, _c2020.
300			_axv, 183 p. : _bill. ; _c23 cm
504			_aIncludes bibliographical references and index
505			_tTOC _a1 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 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 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
520			_aThe growing importance of data science, and the increasing role of information professionals in the management and use of data, are brought together in Practical Data Science for Information Professionals to provide a practical introduction specifically designed for information professionals. 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. Practical Data Science for Information Professionals provides an accessible introduction to data science, using detailed examples and analysis on real data sets to explore the basics of the subject. Content covered includes: the growing importance of data science; the role of the information professional in data science; some of the most important tools and methods that information professionals may use; an analysis of the future of data science and the role of the information professional. 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
526			_aISLM _bISLM
650			_aData services librarians.
650			_aDatabase management in libraries.
856	4	2	_3WorldCat Details _uhttp://explore.bl.uk/primo_library/libweb/action/display.do?frbrVersion=2&tabs=moreTab&ct=display&fn=search&doc=BLL01019826516&indx=1&recIds=BLL01019826516&recIdxs=0&elementId=0&renderMode=poppedOut&displayMode=full&frbrVersion=2&frbg=&&dscnt=0&scp.scps=scope%3A%28BLCONTENT%29&vl(2084770704UI0)=any&tb=t&vid=BLVU1&mode=Basic&srt=rank&tab=local_tab&dum=true&vl(freeText0)=9781783303465&dstmp=1666603852552
942			_2ddc _cTEXT