000			05235cam a2200529Ii 4500
001			ocn920673608
003			OCoLC
005			20190328114812.0
006			m o d
007			cr mn|||||||||
008			150910t20162016maua o 001 0 eng d
040			_aN$T _beng _erda _epn _cN$T _dN$T _dYDXCP _dOCLCO _dIDEBK _dOCLCO _dCDX _dOPELS _dOCLCO _dEBLCP _dOCLCO _dOSU _dOCLCO _dCOO _dOCLCO _dVLB _dOCLCA _dDEBSZ _dOCLCQ _dVT2 _dU3W _dOCLCF _dINT _dOCLCQ _dCOCUF
019			_a920821178 _a929521442 _a989218616
020			_a9780081006719 _qelectronic bk.
020			_a0081006713 _qelectronic bk.
020			_z9780081006634
020			_z0081006632
035			_a(OCoLC)920673608 _z(OCoLC)920821178 _z(OCoLC)929521442 _z(OCoLC)989218616
050		4	_aZ678.85 _b.C69 2016eb
072		7	_aLAN _x025000 _2bisacsh
082	0	4	_a025.1 _223
100	1		_aCox, Brian, _eauthor.
245	1	0	_aHow libraries should manage data : practical guidance on how, with minimum resources, to get the best from your data / _h[electronic resource] _cBrian Cox.
264		1	_aWaltham, MA ; _aKidlington, Ox, UK : _bChandos Publishing is an imprint of Elsevier, _c2016.
264		4	_c�2016
300			_a1 online resource (ix, 137 pages) : _billustrations.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
490	1		_aChandos information professional series.
500			_aIncludes index.
520			_aHave you ever looked at your Library's key performance indicators and said to yourself "so what!"? Have you found yourself making decisions in a void due to the lack of useful and easily accessible operational data? Have you ever worried that you are being left behind with the emergence of data analytics? Do you feel there are important stories in your operational data that need to be told, but you have no idea how to find these stories? If you answered yes to any of these questions, then this book is for you. How Libraries Should Manage Data provides detailed instructions on how to transform your operational data from a fog of disconnected, unreliable, and inaccessible information - into an exemplar of best practice data management. Like the human brain, most people are only using a very small fraction of the true potential of Excel. Learn how to tap into a greater proportion of Excel's hidden power, and in the process transform your operational data into actionable business intelligence.
505	0		_aFront Cover; How Libraries Should Manage Data; Copyright Page; Dedication; Contents; About the author; 1 Introduction; 2 Lifting the fog; First steps -- project management; 3 Step away from the spreadsheet -- common errors in using spreadsheets, and their ramifications; The ten table commandments; 4 Starting from scratch; How low do you go?; Measuring loans and accounting for variation; Visits and how to organize the data into columns; Browsed items and avoiding false conclusions; 5 Getting the most out of your raw data; Keep it simple stupid!
505	8		_aMake it easy stupid! Absolute and relative formulasFormulas you must know; Typical error messages and what they mean; Managing error messages; 6 Stop, police!; Protecting data; Data validation; Using tables; Using a table to populate a validation list; Dependent lookups; 7 Pivot magic; How to create a pivot table; Anatomy of a pivot table; Bringing it all together; Set up the Contents sheet; Set up the Pivot sheet; Set up the RawData sheet; Set up the Validation sheet; Done!; 8 Moving beyond basic pivots; Relational databases; PowerPivot; How to use PowerPivot; Adding calculated columns
505	8		_aCreating a PowerPivot PivotTableThe difference between a measure and a calculated column; Adding a measures; 9 How to create your own desktop library cube; Making the "desktop cube"; Sourcing the datasets; Using MS Access to create a merged dataset; Linking PowerPivot to the merged dataset; Adding a few more tables; IP address table; Resources table; Frequency table; Date table; Adding calculated columns to PowerPivot; FormattedDate; ResourceUsed; KeyMinutesActive; FrequencyMinutesTotal; KeyYearMonthDay; FrequencyMinutesDay; Location; GroupMinutesDay; GroupMinutesTotal; Creating relationships
505	8		_aWriting measuresDistinctStudents; MinutesActive; AverageMark; Some suggested views; Minutes of usage by resource accessed and faculty; Frequency distribution of student usage of resources by faculty; Frequency usage by hours; Average mark by frequency of library usage; 10 Beyond the ordinary; Index; Back Cover
588			_aDescription based on print version record.
650		0	_aLibraries _xEvaluation.
650		0	_aQuantitative research _xLibraries.
650		7	_aLANGUAGE ARTS & DISCIPLINES / Library & Information Science / General _2bisacsh
650		7	_aLibraries _xEvaluation. _2fast _0(OCoLC)fst00997397
655		4	_aElectronic books.
655		0	_aElectronic books.
776	0	8	_iPrint version: _aCox, Brian. _tHow libraries should manage data. _dWaltham, MA Elsevier Chandos Publishing, [2016] _z9780081006634
830		0	_aChandos information professional series.
856	4	0	_3ScienceDirect _uhttp://www.sciencedirect.com/science/book/9780081006634
999			_c247159 _d247159