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Data Clean-Up and Management

Book Description

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

Table of Contents

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