Data Clean-Up and Management: A Practical Guide for Librarians
Data 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 librarians - Deals with practical, real-life issues and addresses common problems that all libraries face - Offers cradle-to-grave treatment for preparing and using data, including download, clean-up, management, analysis and presentation
1112546828
Data Clean-Up and Management: A Practical Guide for Librarians
Data 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 librarians - Deals with practical, real-life issues and addresses common problems that all libraries face - Offers cradle-to-grave treatment for preparing and using data, including download, clean-up, management, analysis and presentation
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Data Clean-Up and Management: A Practical Guide for Librarians

Data Clean-Up and Management: A Practical Guide for Librarians

Data Clean-Up and Management: A Practical Guide for Librarians

Data Clean-Up and Management: A Practical Guide for Librarians

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Overview

Data 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 librarians - Deals with practical, real-life issues and addresses common problems that all libraries face - Offers cradle-to-grave treatment for preparing and using data, including download, clean-up, management, analysis and presentation

Product Details

ISBN-13: 9781780633473
Publisher: Chandos Publishing
Publication date: 10/22/2012
Series: Chandos Information Professional Series
Sold by: Barnes & Noble
Format: eBook
Pages: 578
File size: 22 MB
Note: This product may take a few minutes to download.

About the Author

Margaret Hogarth is Electronic Resources Coordinator and Subject Specialist for Environmental Sciences, Water and Soils for the University of California, Riverside Libraries. She has a B.A. in English from the University of California, Santa Barbara, an MLIS from San Jose State University and an M.S. in Environmental Studies from California State University, Fullerton. She has been a librarian since 1999.Kenneth Furuta, a Reference/Information Technology librarian for the University of California, Riverside Libraries. His B.A. was a double major in Psychology & Music from the University of California, Riverside. In addition to his MLS from the University of Arizona he has a Masters of Administration (emphasis in Management Information Systems) from UC Riverside. He has been a librarian since 1990.

Table of Contents

- List of figures - List of tables - About the authors - Chapter 1: Introduction (why this book is needed) - Abstract: - What makes this book unique? - Why library data is important - The book's outline - Chapter 2: Commonalities - Abstract: - Microsoft Office Excel - MarcEdit - Microsoft Access - XML - Commonalities - Capture and use - Standardization - Data import issues - Technical skills - Project management challenges - Chapter 3: Defining data - Abstract: - Rule 1: define data points - Rule 2: apply data point definitions - Rule 3: count the right apples - Rule 4: avoid capturing redundant data - Chapter 4: Types of data issues - Abstract: - Microsoft Excel vs Microsoft Access - General data-handling edicts - Data issues: importing data - Chapter 5: Microsoft Excel techniques - Abstract: - Creating datasheets - Selecting cells - Copying - Sorting - Filter - AutoSum - Sum - Fill - Chapter 6: Data clean-up in Excel - Abstract: - Common dirty data scenarios - The usefulness of delimiting - System limitations - Removing extra characters - Chapter 7: Excel: combining data - Abstract: - IF statements - The TEXT function - PivotTables and filtering - VLOOKUP - HLOOKUP - MATCH - Chapter 8: Additional tools - Abstract: - PDFs - Notepad - Microsoft Word - Global update in an integrated library system - Regular expressions - Excel - Access - Macros - XML - MarcEdit - The MARC tools window - Chapter 9: Access techniques - Abstract: - What is a database? - Access - Planning a database - Preparing data for a database - Adding a table to a database - Chapter 10: Access forms - Abstract: - Types of form - Parts to a form - Form controls - Validating data - Option buttons - Combo boxes - For a Spin Button: - Tab control techniques - Multiple-table forms - Chapter 11: Access reports - Abstract: - Creating a report using the Report Wizard - Controls - Making additions to a report - AutoFormat a report - Working with report properties - Inserting 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 - Chapter 12: Access queries - Abstract: - Sorting in Access - Filtering in Access - Queries - Entering data - Query properties - Access relationships - Chapter 13: Data clean-up in Access - Abstract: - Prevention is the best cure - Extra characters - Access data upload errors - ISSN issues - Chapter 14: Access -- combining data - Abstract: - Combining data from one or moredata sources - Query with a sum - Types of operators - Totals 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 - Chapter 15: Strategies for missing data - Abstract: - Resources are missing ISBNs - Resources are missing ISSNs - Richard Jackson's OCLC look-up strategy - Chapter 16: Qualitative data - Abstract: - The definition of qualitative data - Qualitative data is valuable - Types of qualitative data - Qualitative data techniques - SWOT analysis - Tools - The whole picture - Chapter 17: ROI - Abstract: - Chapter 18: Data collection and analysis - Abstract: - What data do you need to answer the question? - Does the data measure what you need to measure? - Analysing data - Data presentation - Charts - Stacked charts - Chapter 19: Data quality policy - Abstract: - Poor data quality - Data as an asset and a product - Apply quality principles - Process design - Framework for a data quality policy - Chapter 20: Next steps - Abstract: - Appendix 1: Excel techniques - Appendix 2: Excel functions - Appendix 3: Access quick keys - Appendix 4: Redman's model data policy - Bibliography and references - Index
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