Database Cleanup - Susanne Petersson

Susanne Petersson

Project Manager, Chicago Art Deco Society

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

A Clean Database is

Susanne Petersson 4

Develop protocol based on:

� Reasons for a clean database

� Fields to clean

� When to cleanse a database

Susanne Petersson 5

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

Susanne Petersson 6


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

Susanne Petersson 7


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

Susanne Petersson 8


Rate of Internal/External

Forces …

Susanne Petersson 9


Rate of Internal/External

Forces shall continue

to Increase

Susanne Petersson 10


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



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




� Fields to clean



Database Fields to Clean

Those key to identifying:

Errors

� Typographical

Inconsistencies

� Duplicates

� Incomplete data

� Field formattingSusanne Petersson 14


The core fields are:

Street (Address 1)

Unit (Address 2)

State (province, territory)

Country

It is that Simple.. Susanne Petersson 15


Standardize these first:

Street (Address 1)

Unit (Address 2)

State (province, territory)

Country

… … … … and then Susanne Petersson 16


Organize the data to:

� Fix errors

� Address inconsistencies

� Expand search to other fields



1. Standardize: Street (Address 1)

Abbreviate the direction

Abbreviate the street type

No periods needed



2. Standardize: Unit (Address 2)

Remove terms associated with multi-unit tenancy

Replace verbiage with the symbol “#”



3. Standardize: State (Province, Territory)

Maximum of 2 to 4 alpha-characters

Abbreviations are accepted standard world-wide

No periods necessary



4. Standardize: Country

Consider leaving field empty, as appropriate

Maximum of 2 to 8 alpha-characters

No periods necessary



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



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



Benefits of standardization

Analytics

– Accurate counts: memberships,

contributions

– Proper analysis: demographics,

activity



Benefits of standardization

Communications

– Data fits well on forms

– Offers a professional look and feel




� Fields to clean



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



Based on integrity expectationsBased on integrity expectationsBased on integrity expectationsBased on integrity expectations

� Accuracy

� Consistency

� Relevancy



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



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




As notified – triggered by user activity

Accuracy-Consistency-Relevance: 60% +

� Activity accomplished in the midst of

other task assignments




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




As needed – 1 week prior to significant

event


� Quickly identify field inconsistencies

� Bound by some time constraints



b.b.b.b. Planned schedules Planned schedules Planned schedules Planned schedules

Quarterly – regular maintenance

� Review bulk of records



inconsistencies




Quarterly – regular maintenance



� Adequate time allotted for thoroughness




Annually – confirm statistics

� Review all records



inconsistencies




Annually – confirm statistics



� Adequate time allotted for thoroughness


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 ..


• 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?


• 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




• Secure your dataSecure your dataSecure your dataSecure your data

Firewall – SaaS or personal system

Backup files – local, cloud

Activate anti-virus software




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!


Susanne Petersson

Project Manager, Chicago Art Deco Society

Date post:	12-Apr-2017
Category:	Data & Analytics
Upload:	susanne-petersson-lssgb
View:	303 times
Download:	0 times

Database Cleanup - Susanne Petersson

Data & Analytics