How libraries should manage data practical guidance on how, with minimum resources, to get the best from your data /

Have 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 emergen...

Full description

Main Author: Cox, Brian,
Other Authors: ScienceDirect (Online service)
Format: eBook
Language: English
Published: Waltham, MA ; Kidlington, Ox, UK : Chandos Publishing is an imprint of Elsevier, [2016]
Physical Description: 1 online resource (ix, 137 pages) : illustrations.
Series: Chandos information professional series.
Subjects:
Table of Contents:
  • Front 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!
  • Make 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.
  • Creating 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.
  • Writing 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.