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| 020 | $a9781843346722 (pbk.) | |
| 020 | $a1843346729 (pbk.) | |
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| 100 | 1_ | $aHogarth, Margaret. |
| 245 | 10 | $aData clean-up and management :$ba practical guide for librarians /$cMargaret Hogarth with contributions from Kenneth Furuta. |
| 264 | _1 | $aOxford :$bChandos Publishing,$c2012. |
| 300 | $axxxix, 578 pages :$billustrations ;$c24 cm | |
| 336 | $atext$btxt$2rdacontent | |
| 337 | $aunmediated$bn$2rdamedia | |
| 338 | $avolume$bnc$2rdacarrier | |
| 504 | $aIncludes bibliographical references (pages 527-531) and index. | |
| 505 | 0_ | $aIntroduction (why this book is needed) -- Commonalities -- Defining data -- Types of data issues -- Microsoft Excel techniques -- Data clean-up in Excel -- Excel: combining data -- Additional tools -- Access techniques -- Access forms -- Access reports -- Access queries -- Data clean-up in Access -- Access – combining data -- Strategies for missing data -- Qualitative data -- ROI -- Data collection and analysis -- Data quality policy -- Next steps. |
| 650 | _0 | $aData editing. |
| 650 | _0 | $aLibraries$xData processing. |
| 700 | 1_ | $aFuruta, Kenneth. |
| 997 | $aMARCIVE | |
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| 035 | $a(CaSebORM)9781843346722 | |
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| 082 | 00 | $a025$a025.210285 |
| 090 | $aZ678.9$b.H643 2012 | |
| 100 | 1_ | $aHogarth, Margaret. |
| 245 | 10 | $aData clean-up and management :$ba practical guide for librarians /$cMargaret Hogarth with contributions from Kenneth Furuta. |
| 250 | $a1st edition | |
| 264 | _1 | $aOxford :$bChandos Publishing,$c2012. |
| 300 | $a1 online resource (579 p.) | |
| 336 | $atext$btxt | |
| 337 | $acomputer$bc | |
| 338 | $aonline resource$bcr | |
| 347 | $atext file | |
| 440 | _0 | $aChandos information professional series |
| 500 | $aDescription based upon print version of record. | |
| 505 | 0_ | $aCover; Data Clean-up and Management: A practical guide for librarians; Copyright; Contents; List of figures; List of tables; About the authors; 1 Introduction (why this book is needed); What makes this book unique?; Why library data is important; The book's outline; 2 Commonalities; Microsoft Office Excel; MarcEdit; Microsoft Access; XML; Commonalities; Capture and use; Standardization; Data import issues; Technical skills; Project management challenges; 3 Defining data; Rule 1: define data points; Rule 2: apply data point definitions; Rule 3: count the right apples |
| 505 | 8_ | $aRule 4: avoid capturing redundant data4 Types of data issues; Microsoft Excel vs Microsoft Access; General data-handling edicts; Data issues: importing data; 5 Microsoft Excel techniques; Creating datasheets; Selecting cells; Copying; Sorting; Filter; AutoSum; Sum; Fill; 6 Data clean-up in Excel; Common dirty data scenarios; The usefulness of delimiting; System limitations; Removing extra characters; 7 Excel: combining data; IF statements; The TEXT function; PivotTables and filtering; VLOOKUP; HLOOKUP; MATCH; 8 Additional tools; PDFs; Notepad; Microsoft Word |
| 505 | 8_ | $aGlobal update in an integrated library systemRegular expressions; Excel; Access; Macros; XML; MarcEdit; The MARC tools window; 9 Access techniques; What is a database?; Access; Planning a database; Preparing data for a database; Adding a table to a database; 10 Access forms; Types of form; Parts to a form; Form controls; Validating data; Option buttons; Combo boxes; ActiveX controls; Tab control techniques; Multiple-table forms; Command buttons; 11 Access reports; Creating a report using the Report Wizard; Controls; Making additions to a report; AutoFormat a report |
| 505 | 8_ | $aWorking with report propertiesInserting a control into a report; Conditional formatting; Sizing reports; Moving controls in Access; Publishing reports; Sorting and grouping options; Adding calculations to reports; Launching reports; Creating a subreport; 12 Access queries; Sorting in Access; Filtering in Access; Queries; Entering data; Query properties; Access relationships; 13 Data clean-up in Access; Prevention is the best cure; Extra characters; Access data upload errors; ISSN issues; 14 Access - combining data; Combining data from one or more data sources; Query with a sum |
| 505 | 8_ | $aTypes of operatorsTotals queries; Parameter queries; Action queries; Update queries; Delete queries; Make-Table queries; Append queries; PivotTable queries; SQL in Access; Parameter Queries in SQL; Export data to Excel; Finding unique values in a dataset; Matching on ISSN; 15 Strategies for missing data; Resources are missing ISBNs; Resources are missing ISSNs; Richard Jackson's OCLC look-up strategy; 16 Qualitative data; The definition of qualitative data; Qualitative data is valuable; Types of qualitative data; Qualitative data techniques; SWOT analysis; Tools; The whole picture; 17 ROI |
| 505 | 8_ | $a18 Data collection and analysis |
| 520 | $aData use in the library has specific characteristics and common problems. Data Clean-up and Management addresses these, and provides methods to clean up frequently-occurring data problems using readily-available applications. The authors highlight the importance and methods of data analysis and presentation, and offer guidelines and recommendations for a data quality policy. The book gives step-by-step how-to directions for common dirty data issues.Focused towards libraries and practicing librariansDeals with practical, real-life issues and addresses common problems th | |
| 546 | $aEnglish | |
| 504 | $aIncludes bibliographical references and index. | |
| 588 | $aDescription based on online resource; title from PDF title page (ebrary, viewed December 26, 2013). | |
| 650 | _0 | $aLibraries$xData processing. |
| 650 | _0 | $aData editing. |
| 776 | $z1-84334-672-9 | |
| 700 | 1_ | $aFuruta, Kenneth. |
| 830 | _0 | $aChandos Information Professional Series |
| 906 | $aBOOK | |