Database cleansing can be quite daunting and confusing. Ignoring simple determinants, such as whether to abbreviate a field, can result in duplicate records, incomplete sorting, missing data, and even typographical errors - all leading to irrelevant and useless data. Concentrate on these 4 fields of your membership database to maintain accuracy, consistency, and relevancy. Follow this methodology to ensure your database remains the basis for decision-making and instrumental in achieving your non-profit goals.

1. Susanne Petersson
Project Manager, Chicago Art Deco Society

2. Membership = Customers
Members are our Fans !
Members are our
Bread and Butter !
http://mrshealy-usii.wikispaces.com Susanne Petersson 2

3. Membership = Customers
Members are our Fans !
Members are our
Bread and Butter !
………… manage Member
information with diligence
http://mrshealy-usii.wikispaces.com Susanne Petersson 3

4. A Clean Database is:
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5. Reasons for a Clean
Database
Database Fields to
Clean
When to Cleanse a
Database
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6. Reasons for a Clean Database
A. Data is captured/modified by
other areas
B. Data is included in decision-
making
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7. Reasons for a Clean Database
A. Data is captured internally
Mailings of publications, thank-you gifts
Direct communications (letters)
Email announcements
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8. Reasons for a Clean Database
A. Data is modified externally
Members enter, update
their own data
Non-members join events,
request information
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9. Susanne Petersson 9
Rate of Internal/External
Forces …

10. Rate of Internal/External
Forces shall continue
to Increase
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11. Reasons for a Clean Database
B. Data is included in decision-making
Affects your non-profit goals
Uncovers strategic opportunities
Influences recurring activities
Impacts financials
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12. Reasons for a Clean Database
B. Data is included in decision-making –
and decision-making is based on..
Accurate Statistics
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13. Reasons for a Clean
Database
Database Fields to
Clean
When to Cleanse a
Database
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14. Database Fields to Clean
Those key to identifying:
Errors
Typographical
Inconsistencies
Duplicates
Incomplete data
Field formatting
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15. Database Fields to Clean
The core fields are:
Street (Address 1)
Unit (Address 2)
State (province, territory)
Country
It is that Simple..
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16. Database Fields to Clean
Standardize these first:
Street (Address 1)
Unit (Address 2)
State (province, territory)
Country
………… and then
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17. Database Fields to Clean
Organize the data to:
Fix errors
Address inconsistencies
Expand search to other fields
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18. Database Fields to Clean
1. Standardize: Street (Address 1)
Abbreviate the direction
Abbreviate the street type
No periods needed
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19. Database Fields to Clean
2. Standardize: Unit (Address 2)
Remove terms associated with multi-unit
tenancy
Replace verbiage with the symbol “#”
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20. Database Fields to Clean
3. Standardize: State (Province, Territory)
Maximum of 2 to 4 alpha-characters
Abbreviations are accepted standard
world-wide
No periods necessary
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21. Database Fields to Clean
4. Standardize: Country
Consider leaving field empty, when
unnecessary
Maximum of 2 to 8 alpha-characters
No periods necessary
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22. The ability to retain a
clean database is based
on consistency
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23. The 4 core fields are
used as the base
structure to sort data
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24. Database Fields to Clean
Benefits of standardization
Analytics
– Accurate counts: memberships,
contributions
– Proper analysis: demographics,
activity
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25. Database Fields to Clean
Benefits of standardization
Communications
– Data fits well on forms
– Offers a professional look and feel
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26. Reasons for a Clean
Database
Database Fields to
Clean
When to Cleanse a
Database
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27. When to Cleanse a Database
Dependent upon
Database size [number of records]
Significant events – financial, social,
marketing
Number of persons altering data
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28. When to Cleanse a Database
Based on integrity expectations
Accuracy
Consistency
Relevancy
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29. When to Cleanse a Database
Two types of schedules
a. Ad hoc
As notified
As needed
b. Planned
Quarterly
Annually
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30. When to Cleanse a Database
a. Ad hoc schedules
As notified – triggered by user activity
Review individual or small set of records
Generally perform on-line
Focus on core and other contact-related
fields
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31. When to Cleanse a Database
a. Ad hoc schedules
As notified – triggered by user activity
Accuracy-Consistency-Relevance: 60% +
Activity accomplished in the midst of
other task assignments
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32. When to Cleanse a Database
a. Ad hoc schedules
As needed – 1 week prior to significant
event
Review bulk of records
Generally export to spreadsheet format
Focus on core fields, name(s), then other
inconsistencies
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33. When to Cleanse a Database
a. Ad hoc schedules
As needed – 1 week prior to significant
event
Accuracy-Consistency-Relevance: 80% +
Quickly identify field inconsistencies
Bound by some time constraints
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34. When to Cleanse a Database
b. Planned schedules
Quarterly – regular maintenance
Review bulk of records
Generally export to spreadsheet format
Focus on core fields, name(s), then other
inconsistencies
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35. When to Cleanse a Database
b. Planned schedules
Quarterly – regular maintenance
Accuracy-Consistency-Relevance: 90% +
Quickly identify field inconsistencies
Adequate time allotted for thoroughness
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36. When to Cleanse a Database
b. Planned schedules
Annually – confirm statistics
Review all records
Generally export to spreadsheet format
Focus on core fields, name(s), then other
inconsistencies
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37. When to Cleanse a Database
b. Planned schedules
Annually – confirm statistics
Accuracy-Consistency-Relevance: 98% +
Quickly identify field inconsistencies
Adequate time allotted for thoroughness
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38. Now that you have
completed the process:
Identified reasons for accuracy
Determined the fields to monitor
Established recurring schedules
… a note about Security..
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39. Do you know what
may be
heading your way?
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40. Data is the lifeblood of your
organization
Other departments rely on it
Accurate data is easily
navigated
Users expect to see relevant
data
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41. Secure your system and
pc data
Protect with a firewall
Backup files – local, cloud
Activate anti-virus software
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42. My name is Susanne Petersson
I assisted the Chicago Art Deco Society to develop
repeatable processes to manage the membership
database.
As a LSSGB and MBA, I understand corporate
dynamics
As a project manager, I get things done
As a certified trainer, I understand and value the
human element
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43. Thank you!Thank you!Thank you!Thank you!
SPetersson.usa@gmail.comSPetersson.usa@gmail.comSPetersson.usa@gmail.comSPetersson.usa@gmail.com
SusanneSusanneSusanneSusanne----PeterssonPeterssonPeterssonPetersson----USAUSAUSAUSA