SETA (regional) Conference

1
SETA (regional) Conference

• Seeing Double? Focus on it.
• Presenters Natalie Spooner Sue Wadhams
• Session 4 Monday, September 19th, 215pm

2
Session Rules of Etiquette

• Please turn off your cell phone/beeper
• If you must leave the session early, please do so
  as discretely as possible
• Please avoid side conversation during the
  presentation
• Thank you for your cooperation!

3
Introduction

• Purpose
• Share an SSN housekeeping strategy in Plus, for
  those using CWID option 1 or 2.
• Benefits
• Get rid of dead wood on Plus files.
• Convert minimal number of records to Banner.
• Expose sources of bad data.
• Opportunity to improve office procedures
  regarding entry of SSNs.
• Heed advice to clean up data on Plus before our
  Leap to Banner.

4
Topics of Discussion

• Duplicate SSN background
• Focexec DUPLSSN walk-thru
• Fun with results look for patterns

5
Duplicate SSN background

• Converted to Plus in 1992
• Have about 100,000 records on AAFILE
• Defined DUPLICATES as students with matching
  birth dates and first 14 characters of name.
• Found well over 1,000 pairs of duplicates (with
  some triplicates)
• DO SOMETHING to clean them up before Banner
  conversion

6
Focexec DUPLSSN walk-thru

• Step 1 create hold file 1 of all records on
  AAFILE with 22-char key (8-digit birthdate
  first 14 of name)
• where birthdate is not zero
• where bypass conversion flag is not set
• Sum by 22-char key

7
Focexec DUPLSSN walk-thru

• Step 2 create hold file 2 of all records on
  AAFILE with 22-char key
• where birthdate is not zero
• where bypass conversion flag is not set
• include counters/indicators that show how
  embedded SSN is in PLUS

8
Focexec DUPLSSN walk-thru

• Step 3 Join hold file 1 to ALL records in hold
  file 2
• Count number of matches
• Create hold file 3 of records in hold file 1
  with more than 1 match.
• Step 4 Join hold file 3 to ALL records in hold
  file 2
• Print report of duplicates/triplicates
• Data columns

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Focexec DUPLSSN walk-thru

• IDENTIFYING DATA
• Birthdate
• Full name (first 14 will match)
• SSN
• Previous SSN, if any
• Gender
• Ethnicity
• Military status
• Previous name, if any

• WHERE EMBEDDED
• SR seg 050 counter (011, 1E1)
• AP seg 060 counter (110)
• BS seg 070 counter (404)
• MM indicator (2E5/206)
• RA indicator (118/123)
• RB indicator (209/211/221)
• FAM indicator (3xx)

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Focexec DUPLSSN walk-thru

• 2E5 118 209
• 1E1 110 404 206 123 211 3XX
• SR AP BS MM RA RB FAM
• CNT CNT CNT IND IND IND IND
• ----- ----- ----- ----- ----- ----- -----
• 1 1 1 N Y N N
• 0 0 0 N Y N N

11
Focexec DUPLSSN walk-thru


F
S A B M R R
A
R P S M A B M
------------------------------- 1975
/01/01 Netto, James E 123456789 1 1 1
N Y Y N Netto, James Edward
012345678 0 0 0 N N N N
Delete bad SSN. 1976/01/01 Condino, Sandra
Jean 123123123 1 2 1 Y Y Y
Y Condino, Sandra Keegan 123123124 1 0
0 N N N N Delete bad
SSN. 1977/01/01 Trocchi, Chris 010101010
0 0 0 N N N Y Trocchi,
Christian A 110101010 1 1 1 Y Y
N N Financial Aid review delete bad SSN.



12
Focexec DUPLSSN walk-thru

F
S A B M R R A
R
P S M A B M
------------------------------- 1978/01/0
1 Dingman, Megan M. 123456789 1 1 1
N Y Y N Dingman, Megan Marissa
012345678 0 0 0 N Y N N
Registrar review delete bad SSN. 1979/01/01
Ryan, Melissa A 123123123 1 2 1 Y
Y Y Y Ryan, Melissa Ann 111222333
1 0 1 N N N N Bursar review
set flag to bypass conversion. 1980/01/01
Collazo, Cesar JR 010101010 0 0 0 Y
N Y N Collazo, Cesar, JR 110101010
1 1 1 Y Y N N Admissions
review delete bad SSN.
13
Focexec DUPLSSN walk-thru

F
S A B M R R A
R
P S M A B M
------------------------------- 1981/01/0
1 Khandadash, Ari M 123456788 1 1
1 N Y N N Khandadash, Ariela F
123456789 1 1 1 N Y N N These
are twins. 1982/01/01 Williams, John A
000111222 1 1 1 N Y N N
Williams, John B 222111000 1 1 1
N Y N N These are not the same person.
14
Fun with results look forpatterns

• 000NNNN - use screen 012 to delete bad SSN.
• 100NNNN - use screen 012 to delete bad SSN.
• We had so many of these that we ran a separate
  focus to create 02D (delete student) batch
  maintenance cycle transactions.

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Fun with results look for patterns

• 000NNNY Financial Aid review. Use SBA910 to
  delete bad SSN in batch use screen 012 to delete
  bad SSN.
• 000YNNN Admissions review. Put admissions data
  on good SSN delete admissions data on bad SSN
  use screen 012 to delete bad SSN.
• 000YNYN same as above.

16
Fun with results look for patterns

• 000NYNN Registrar review. Put screen 123 data
  on good SSN use screen 012 to delete bad SSN.
• 101NNNN Bursar review. Set flag to bypass
  during conversion.

17
Fun with results look for patterns

• Watch out for twins, and matches that are not
  truly the same person
• Vary the 14-char name match to improve accuracy
• Create a version of DUPLSSN for Admissions so
  they can do their own housekeeping

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Summary

• Demonstrated our SSN housekeeping strategy, which
  may be useful to other Plus schools with CWID
  option 1 or 2.
• Benefits
• Get rid of dead wood on Plus files.
• Convert minimal number of records to Banner.
• Expose sources of bad data.
• Opportunity to improve office procedures
  regarding entry of SSNs.
• Clean data on Plus before Leap to Banner.

19
Questions and Answers

• Anyone ????

20
Presenter Information

• Natalie Spooner,Registrar
• nspooner_at_sunyjefferson.edu
• Sue Wadhams, Systems Analyst swadhams_at_sunyjeffer
  son.edu
• Jefferson Community College
• 1220 Coffeen Street
• Watertown, NY 13601