1. Collections Management Museums EMu – Data Cleaning with EMu Data Cleaning with EMu Warren Hindley

2. Collections Management Museums EMu – Data Cleaning with EMu Why Bother? Minimise data replication, EMu is relational. Speed.  Data entry sorting and selecting records. Processing of large numbers of records  For reports or labels.  Lookup Lists are populated from data in records. Quality Data – Turn data into information

3. Collections Management Museums EMu – Data Cleaning with EMu Lookup Lists

4. Collections Management Museums EMu – Data Cleaning with EMu How long does it take? Ages! Make all users aware. Find commonalities. Don’t rush, keep narrowing your result set.  Save Groups of Records

5. Collections Management Museums EMu – Data Cleaning with EMu Examples - Query

6. Collections Management Museums EMu – Data Cleaning with EMu Results Duplicate Records

7. Collections Management Museums EMu – Data Cleaning with EMu Sort Sort results for easier viewing

8. Collections Management Museums EMu – Data Cleaning with EMu Sort Summary Duplicated Records

9. Collections Management Museums EMu – Data Cleaning with EMu Merge

10. Collections Management Museums EMu – Data Cleaning with EMu Merge

11. Collections Management Museums EMu – Data Cleaning with EMu Why not? Worried about deleting records.  Export the data (backup).  Change record status.  Change record permissions. Easy to corrupt data.  Use a small numbers of records.  Experiment with test data, most institutions have training or test systems.

12. Collections Management Museums EMu – Data Cleaning with EMu Changing the Record Status Summary Data and Record Status updated.

13. Collections Management Museums EMu – Data Cleaning with EMu Attachments Search every attachment field in every module for this particular record.

14. Collections Management Museums EMu – Data Cleaning with EMu Attachments 870 Attachments To the catalogue.

15. Collections Management Museums EMu – Data Cleaning with EMu Global Replace Replace a value in one or more fields with another. It can be used to:  Correct spelling mistakes.  Change the case of text.  Replace Attachments.  Remove Spaces from between text.

16. Collections Management Museums EMu – Data Cleaning with EMu Regular Expressions Special text string for describing a search pattern. Advanced wildcards. They are ugly.

17. Collections Management Museums EMu – Data Cleaning with EMu Global Replace Simple Task: Replace: Ben with Benjamin

18. Collections Management Museums EMu – Data Cleaning with EMu Global Replace

19. Collections Management Museums EMu – Data Cleaning with EMu

20. Collections Management Museums EMu – Data Cleaning with EMu Regular Expressions ^ = Start of the line $ = End of the line

21. Collections Management Museums EMu – Data Cleaning with EMu Support We are here to help, email us: support@man.kesoftware.com