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How libraries should manage data = p...

Cox, Brian,

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

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	How libraries should manage data/ Brian Cox.
其他題名:	practical guidance on how with minimum resources to get the best from your data /
作者:	Cox, Brian,
出版者:	Waltham, MA ;Chandos Publishing is an imprint of Elsevier, : 2016.,
面頁冊數:	1 online resource (ix, 137 p.) :ill.
附註:	Includes index.
內容註:	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!
內容註:	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
內容註:	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
內容註:	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
標題:	Libraries - Evaluation. -
電子資源:	https://www.sciencedirect.com/science/book/9780081006634
ISBN:	9780081006719 (electronic bk.)

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

How libraries should manage datapractical guidance on how with minimum resources to get the best from your data /[electronic resource] :Brian Cox. - Waltham, MA ;Chandos Publishing is an imprint of Elsevier,2016. - 1 online resource (ix, 137 p.) :ill. - Chandos information professional series.. - Chandos information professional series..

Includes index.

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!

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 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.

ISBN: 9780081006719 (electronic bk.)Subjects--Topical Terms:

1580906
Libraries
--Evaluation.Index Terms--Genre/Form:

542853
Electronic books.

LC Class. No.: Z678.85 / .C69 2016eb

Dewey Class. No.: 025.1

How libraries should manage data = practical guidance on how with minimum resources to get the best from your data /
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505 8 $a 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
505 8 $a 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
520 $a 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 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.
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