database cleanup - susanne petersson
TRANSCRIPT
Membership = Customers
Members are our Members are our Members are our Members are our Fans !Fans !Fans !Fans !
Members are our Members are our Members are our Members are our
Bread and Butter !Bread and Butter !Bread and Butter !Bread and Butter !
http://mrshealy-usii.wikispaces.com Susanne Petersson 2
Membership = Customers
Members are our Members are our Members are our Members are our Fans !Fans !Fans !Fans !
Members are our Members are our Members are our Members are our
Bread and Butter !Bread and Butter !Bread and Butter !Bread and Butter !
… manage Member … manage Member … manage Member … manage Member
information with information with information with information with diligencediligencediligencediligence
http://mrshealy-usii.wikispaces.com Susanne Petersson 3
Develop protocol based on:
� Reasons for a clean database
� Fields to clean
� When to cleanse a database
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Reasons for a Clean Database
A.A.A.A. Data is captured/modified by other areasData is captured/modified by other areasData is captured/modified by other areasData is captured/modified by other areas
B.B.B.B. Data is included in decisionData is included in decisionData is included in decisionData is included in decision----makingmakingmakingmaking
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Reasons for a Clean Database
A.A.A.A. Data is captured Data is captured Data is captured Data is captured internallyinternallyinternallyinternally
Mailings of publications, thank-you gifts
Direct communications (letters)
Email announcements
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Reasons for a Clean Database
A.A.A.A. Data is modified Data is modified Data is modified Data is modified externally externally externally externally
Members enter, update their
own data
Non-members join events,
request information
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Reasons for a Clean Database
Rate of Internal/External
Forces shall continue
to Increase
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Reasons for a Clean Database
B.B.B.B. Data is included in decisionData is included in decisionData is included in decisionData is included in decision----makingmakingmakingmaking
Affects your non-profit goals
Uncovers strategic opportunities
Influences recurring activities
Impacts financials
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Reasons for a Clean Database
B.B.B.B. Data is included in decisionData is included in decisionData is included in decisionData is included in decision----making making making making ––––
and decisionand decisionand decisionand decision----making is based on..making is based on..making is based on..making is based on..
Accurate Statistics
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Develop protocol based on:
� Reasons for a clean database
� Fields to clean
� When to cleanse a database
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Database Fields to Clean
Those key to identifying:
Errors
� Typographical
Inconsistencies
� Duplicates
� Incomplete data
� Field formattingSusanne Petersson 14
Database Fields to Clean
The core fields are:
Street (Address 1)
Unit (Address 2)
State (province, territory)
Country
It is that Simple.. Susanne Petersson 15
Database Fields to Clean
Standardize these first:
Street (Address 1)
Unit (Address 2)
State (province, territory)
Country
… … … … and then Susanne Petersson 16
Database Fields to Clean
Organize the data to:
� Fix errors
� Address inconsistencies
� Expand search to other fields
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Database Fields to Clean
1. Standardize: Street (Address 1)
Abbreviate the direction
Abbreviate the street type
No periods needed
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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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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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Database Fields to Clean
4. Standardize: Country
Consider leaving field empty, as appropriate
Maximum of 2 to 8 alpha-characters
No periods necessary
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Database Fields to Clean
The ability to retain a clean The ability to retain a clean The ability to retain a clean The ability to retain a clean
database is based on database is based on database is based on database is based on
consistencyconsistencyconsistencyconsistency
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Database Fields to Clean
The core fields are used The core fields are used The core fields are used The core fields are used
as the as the as the as the
base structure to sort database structure to sort database structure to sort database structure to sort data
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Database Fields to Clean
Benefits of standardization
Analytics
– Accurate counts: memberships,
contributions
– Proper analysis: demographics,
activity
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Database Fields to Clean
Benefits of standardization
Communications
– Data fits well on forms
– Offers a professional look and feel
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Develop protocol based on:
� Reasons for a clean database
� Fields to clean
� When to cleanse a database
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When to Cleanse a Database
Dependent uponDependent uponDependent uponDependent upon
Database size [number of records]
Significant events – financial, social,
marketing
Number of persons altering data
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When to Cleanse a Database
Based on integrity expectationsBased on integrity expectationsBased on integrity expectationsBased on integrity expectations
� Accuracy
� Consistency
� Relevancy
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When to Cleanse a Database
Two types of schedules Two types of schedules Two types of schedules Two types of schedules
a.a.a.a. Ad hocAd hocAd hocAd hoc
As notified
As needed
b.b.b.b. Planned Planned Planned Planned
Quarterly
Annually
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When to Cleanse a Database
a.a.a.a. Ad hoc schedules Ad hoc schedules Ad hoc schedules 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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When to Cleanse a Database
a.a.a.a. Ad hoc schedules Ad hoc schedules Ad hoc schedules 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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When to Cleanse a Database
a.a.a.a. Ad hoc schedules Ad hoc schedules Ad hoc schedules 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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When to Cleanse a Database
a.a.a.a. Ad hoc schedules Ad hoc schedules Ad hoc schedules 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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When to Cleanse a Database
b.b.b.b. Planned schedules Planned schedules Planned schedules 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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When to Cleanse a Database
b.b.b.b. Planned schedules Planned schedules Planned schedules Planned schedules
Quarterly – regular maintenance
Accuracy-Consistency-Relevance: 90% +
� Quickly identify field inconsistencies
� Adequate time allotted for thoroughness
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When to Cleanse a Database
b.b.b.b. Planned schedules Planned schedules Planned schedules 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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When to Cleanse a Database
b.b.b.b. Planned schedules Planned schedules Planned schedules Planned schedules
Annually – confirm statistics
Accuracy-Consistency-Relevance: 98% +
� Quickly identify field inconsistencies
� Adequate time allotted for thoroughness
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Now that you have completed the process:
� Identified reasons for accuracy of your
database
� Determined the fields to monitor
� Established your recurring schedules
… a note about Security ..
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• Data is the lifeblood of your Data is the lifeblood of your Data is the lifeblood of your Data is the lifeblood of your
organizationorganizationorganizationorganization
• Secure your dataSecure your dataSecure your dataSecure your data
Do you know what may Do you know what may Do you know what may Do you know what may
be heading your way?be heading your way?be heading your way?be heading your way?
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• Data is the lifeblood of your Data is the lifeblood of your Data is the lifeblood of your Data is the lifeblood of your
organizationorganizationorganizationorganization
Other departments rely on it
Accurate data is easily navigated
Users expect to see relevant data
Do you know what may Do you know what may Do you know what may Do you know what may
be heading your way?be heading your way?be heading your way?be heading your way?
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• Secure your dataSecure your dataSecure your dataSecure your data
Firewall – SaaS or personal system
Backup files – local, cloud
Activate anti-virus software
Do you know what may Do you know what may Do you know what may Do you know what may
be heading your way?be heading your way?be heading your way?be heading your way?
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My name is Susanne Petersson
I am assisting 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 certified trainer, I understand and value the human element
Thank you for viewing this presentation!
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