LEADER 05509nam 2200709 450 001 9910462570303321 005 20200520144314.0 010 $a1-78063-347-5 035 $a(CKB)2670000000356496 035 $a(EBL)1579917 035 $a(OCoLC)866442355 035 $a(SSID)ssj0000967885 035 $a(PQKBManifestationID)11605383 035 $a(PQKBTitleCode)TC0000967885 035 $a(PQKBWorkID)10995334 035 $a(PQKB)11354375 035 $a(MiAaPQ)EBC1579917 035 $a(CaSebORM)9781843346722 035 $a(PPN)187349401 035 $a(Au-PeEL)EBL1579917 035 $a(CaPaEBR)ebr10816523 035 $a(CaONFJC)MIL549505 035 $a(OCoLC)865578729 035 $a(EXLCZ)992670000000356496 100 $a20131226d2012 uy| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aData clean-up and management $ea practical guide for librarians /$fMargaret Hogarth with contributions from Kenneth Furuta 205 $a1st edition 210 1$aOxford :$cChandos Publishing,$d2012. 215 $a1 online resource (579 p.) 225 0$aChandos information professional series 300 $aDescription based upon print version of record. 311 $a1-84334-672-9 320 $aIncludes bibliographical references and index. 327 $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 327 $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 327 $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 327 $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 327 $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 327 $a18 Data collection and analysis 330 $aData use in the library has specific characteristics and common problems. Data Clean-up and Management addresses these, and provides methods to clean up frequently-occurring data problems using readily-available applications. The authors highlight the importance and methods of data analysis and presentation, and offer guidelines and recommendations for a data quality policy. The book gives step-by-step how-to directions for common dirty data issues.Focused towards libraries and practicing librariansDeals with practical, real-life issues and addresses common problems th 410 0$aChandos Information Professional Series 606 $aLibraries$xData processing 606 $aData editing 608 $aElectronic books. 615 0$aLibraries$xData processing. 615 0$aData editing. 676 $a025 676 $a025.210285 700 $aHogarth$b Margaret$0869690 701 $aFuruta$b Kenneth$0869691 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910462570303321 996 $aData clean-up and management$91941766 997 $aUNINA