Meeting the Demand for Meeting the Demand for Data ProfessionalsData Professionals

Meeting the Demand for Meeting the Demand for Data ProfessionalsData Professionals

Presented atPresented at::

IASSIST/IFDO 2005 IASSIST/IFDO 2005

EdinburghEdinburghMay 2005

Presented atPresented at::

IASSIST/IFDO 2005 IASSIST/IFDO 2005

EdinburghEdinburghMay 2005

February 11, 2004February 11, 2004

Jane FryJane FryCarleton UniversityCarleton University

AndAnd Ernie BoykoErnie Boyko

Retired Statistics Retired Statistics Canada and Nesstar Canada and Nesstar

AmericasAmericas

OutlineOutlineOutlineOutline

Background for this sessionBackground for this session Nature of the demand for data Nature of the demand for data

professionalsprofessionals Strategies for meeting the Strategies for meeting the

demanddemand Using student resourcesUsing student resources Wrap-upWrap-up

Background for this sessionBackground for this session Nature of the demand for data Nature of the demand for data

professionalsprofessionals Strategies for meeting the Strategies for meeting the

demanddemand Using student resourcesUsing student resources Wrap-upWrap-up

IASSIST 2005

Background:Background:Why this session?Why this session?Background:Background:

Why this session?Why this session?

Staff changes are inevitableStaff changes are inevitable IASSIST list discussion on the IASSIST list discussion on the

‘accidental data librarian’‘accidental data librarian’ IASSIST workshopIASSIST workshop Sharing a Canadian training Sharing a Canadian training

initiativeinitiative How to use students to help fill How to use students to help fill

the gap and train graduatesthe gap and train graduates

Staff changes are inevitableStaff changes are inevitable IASSIST list discussion on the IASSIST list discussion on the

‘accidental data librarian’‘accidental data librarian’ IASSIST workshopIASSIST workshop Sharing a Canadian training Sharing a Canadian training

initiativeinitiative How to use students to help fill How to use students to help fill

the gap and train graduatesthe gap and train graduates

IASSIST 2005

Nature of the Nature of the demand for data demand for data

professionalsprofessionals

Nature of the Nature of the demand for data demand for data

professionalsprofessionals Age profile of existing staff…the Age profile of existing staff…the

renewal of IASSISTrenewal of IASSIST Promotions and career changesPromotions and career changes Growth of data servicesGrowth of data services Need to train other staff in the data Need to train other staff in the data

service institutionsservice institutions Seasonal work loadsSeasonal work loads

The bottom line is that we need to be The bottom line is that we need to be able to have a steady flow of data able to have a steady flow of data professionalsprofessionals

Age profile of existing staff…the Age profile of existing staff…the renewal of IASSISTrenewal of IASSIST

Promotions and career changesPromotions and career changes Growth of data servicesGrowth of data services Need to train other staff in the data Need to train other staff in the data

service institutionsservice institutions Seasonal work loadsSeasonal work loads

The bottom line is that we need to be The bottom line is that we need to be able to have a steady flow of data able to have a steady flow of data professionalsprofessionals

IASSIST 2005

Options for meeting the Options for meeting the demand for data demand for data

professionalsprofessionals

Options for meeting the Options for meeting the demand for data demand for data

professionalsprofessionals Hiring new graduates?Hiring new graduates?

From library schools?From library schools? From Social Science programs?From Social Science programs? What criteria should we use?What criteria should we use?

Hiring from other data centres?Hiring from other data centres? Raiding or evolving career paths?Raiding or evolving career paths? Competitive processesCompetitive processes

Hiring new graduates?Hiring new graduates? From library schools?From library schools? From Social Science programs?From Social Science programs? What criteria should we use?What criteria should we use?

Hiring from other data centres?Hiring from other data centres? Raiding or evolving career paths?Raiding or evolving career paths? Competitive processesCompetitive processes

IASSIST 2005

Options for meeting the Options for meeting the demand for data demand for data professionals professionals Cont’dCont’d

Options for meeting the Options for meeting the demand for data demand for data professionals professionals Cont’dCont’d

Training staff from other areasTraining staff from other areas Do they want to ‘do data’?Do they want to ‘do data’? What should you be looking for?What should you be looking for?

Using studentsUsing students Case study will be presentedCase study will be presented

Training staff from other areasTraining staff from other areas Do they want to ‘do data’?Do they want to ‘do data’? What should you be looking for?What should you be looking for?

Using studentsUsing students Case study will be presentedCase study will be presented

IASSIST 2005

Profile of a Pan Canadian Profile of a Pan Canadian Training ExperienceTraining Experience

Profile of a Pan Canadian Profile of a Pan Canadian Training ExperienceTraining Experience

Canada’s Data Liberation Canada’s Data Liberation Initiative (DLI) created a huge Initiative (DLI) created a huge demand for data professionalsdemand for data professionals

Went from ‘zero to 60’ in a very Went from ‘zero to 60’ in a very short timeshort time

Used peer-to-peer training Used peer-to-peer training approach in 1997 to launch DLIapproach in 1997 to launch DLI

In 2003, launched a second In 2003, launched a second ‘Training the Trainer’ initiative ‘Training the Trainer’ initiative (TtT)(TtT)

Canada’s Data Liberation Canada’s Data Liberation Initiative (DLI) created a huge Initiative (DLI) created a huge demand for data professionalsdemand for data professionals

Went from ‘zero to 60’ in a very Went from ‘zero to 60’ in a very short timeshort time

Used peer-to-peer training Used peer-to-peer training approach in 1997 to launch DLIapproach in 1997 to launch DLI

In 2003, launched a second In 2003, launched a second ‘Training the Trainer’ initiative ‘Training the Trainer’ initiative (TtT)(TtT)

IASSIST 2005

Overview of TtTOverview of TtThttp://datalib.library.ualberta.ca/DLI/Train%20thehttp://datalib.library.ualberta.ca/DLI/Train%20the

%20Trainers/%20Trainers/

Overview of TtTOverview of TtThttp://datalib.library.ualberta.ca/DLI/Train%20thehttp://datalib.library.ualberta.ca/DLI/Train%20the

%20Trainers/%20Trainers/

Recognized need for next Recognized need for next generation of leadersgeneration of leaders

Candidates chosen by regional Candidates chosen by regional training co-ordinatorstraining co-ordinators

Three-day leadership Three-day leadership conferenceconference

Emphasis on skill-building and Emphasis on skill-building and communitycommunity

Recognized need for next Recognized need for next generation of leadersgeneration of leaders

Candidates chosen by regional Candidates chosen by regional training co-ordinatorstraining co-ordinators

Three-day leadership Three-day leadership conferenceconference

Emphasis on skill-building and Emphasis on skill-building and communitycommunity

IASSIST 2005

Carleton University Carleton University Data CentreData Centre

Carleton University Carleton University Data CentreData Centre

Our Staffing Situation Our Staffing Situation 2 2 11//3 3 Full Time Full Time 5 Part Time (total of 60 hrs/wk) 5 Part Time (total of 60 hrs/wk) 1 Research Assistant (total 10 hrs/wk)1 Research Assistant (total 10 hrs/wk)

Our Work SituationOur Work Situation We only do dataWe only do data We do not do maps, gov docs, GIS, or We do not do maps, gov docs, GIS, or

reference questions – these are all reference questions – these are all referred elsewherereferred elsewhere

Our Staffing Situation Our Staffing Situation 2 2 11//3 3 Full Time Full Time 5 Part Time (total of 60 hrs/wk) 5 Part Time (total of 60 hrs/wk) 1 Research Assistant (total 10 hrs/wk)1 Research Assistant (total 10 hrs/wk)

Our Work SituationOur Work Situation We only do dataWe only do data We do not do maps, gov docs, GIS, or We do not do maps, gov docs, GIS, or

reference questions – these are all reference questions – these are all referred elsewherereferred elsewhere

IASSIST 2005

Using StudentsUsing StudentsUsing StudentsUsing Students

Why use them? Why use them? They help clients They help clients They do the ‘grunt’ work They do the ‘grunt’ work They cover the desk when FT staff are absentThey cover the desk when FT staff are absent

Who are they? Who are they? 33rdrd year Undergrads with a Social Science year Undergrads with a Social Science

backgroundbackground They must have taken a 2They must have taken a 2ndnd year Stats course year Stats course They must know SPSS.They must know SPSS.

Why use them? Why use them? They help clients They help clients They do the ‘grunt’ work They do the ‘grunt’ work They cover the desk when FT staff are absentThey cover the desk when FT staff are absent

Who are they? Who are they? 33rdrd year Undergrads with a Social Science year Undergrads with a Social Science

backgroundbackground They must have taken a 2They must have taken a 2ndnd year Stats course year Stats course They must know SPSS.They must know SPSS.

IASSIST 2005

Using StudentsUsing Students(cont’d)(cont’d)

Using StudentsUsing Students(cont’d)(cont’d)

Where do they come from?Where do they come from? When we do class presentations we When we do class presentations we

make an announcementmake an announcement Through word of mouth Through word of mouth Some of our regular clientsSome of our regular clients

What do they do? What do they do? Primary task – to help clients Primary task – to help clients Secondary task – to make data sets Secondary task – to make data sets

ready for public useready for public use

Where do they come from?Where do they come from? When we do class presentations we When we do class presentations we

make an announcementmake an announcement Through word of mouth Through word of mouth Some of our regular clientsSome of our regular clients

What do they do? What do they do? Primary task – to help clients Primary task – to help clients Secondary task – to make data sets Secondary task – to make data sets

ready for public useready for public use

IASSIST 2005

Training the StudentsTraining the StudentsTraining the StudentsTraining the Students

Learning Curve Learning Curve very steep, so be gentle and don’t very steep, so be gentle and don’t

scare them off!scare them off!

ScheduleSchedule Short shifts for the first few Short shifts for the first few

weeks (2-4 hr)weeks (2-4 hr) 1 student at a time1 student at a time I do all the trainingI do all the training

Learning Curve Learning Curve very steep, so be gentle and don’t very steep, so be gentle and don’t

scare them off!scare them off!

ScheduleSchedule Short shifts for the first few Short shifts for the first few

weeks (2-4 hr)weeks (2-4 hr) 1 student at a time1 student at a time I do all the trainingI do all the training

IASSIST 2005

Training the StudentsTraining the Students(cont’d)(cont’d)

Training the StudentsTraining the Students(cont’d)(cont’d)

ExercisesExercises Training book - listing all the Training book - listing all the

proceduresprocedures Subset Exercises – based on real life Subset Exercises – based on real life

subsets, with and without errorssubsets, with and without errors Cheat Sheets – beside each Cheat Sheets – beside each

computer listing the most commonly computer listing the most commonly used commandsused commands

Treasure HuntTreasure Hunt To familiarize the students with our To familiarize the students with our

holdingsholdings

ExercisesExercises Training book - listing all the Training book - listing all the

proceduresprocedures Subset Exercises – based on real life Subset Exercises – based on real life

subsets, with and without errorssubsets, with and without errors Cheat Sheets – beside each Cheat Sheets – beside each

computer listing the most commonly computer listing the most commonly used commandsused commands

Treasure HuntTreasure Hunt To familiarize the students with our To familiarize the students with our

holdingsholdings

IASSIST 2005

The Other StudentThe Other StudentThe Other StudentThe Other Student

Who is it?Who is it? A Grad student in the Social SciencesA Grad student in the Social Sciences Must have taken advanced Stats Must have taken advanced Stats

coursescourses Where do we get him/her from?Where do we get him/her from?

Recommendation from profsRecommendation from profs Former Data Centre employeesFormer Data Centre employees Former ClientsFormer Clients

TrainingTraining Same as the undergrad studentsSame as the undergrad students

Who is it?Who is it? A Grad student in the Social SciencesA Grad student in the Social Sciences Must have taken advanced Stats Must have taken advanced Stats

coursescourses Where do we get him/her from?Where do we get him/her from?

Recommendation from profsRecommendation from profs Former Data Centre employeesFormer Data Centre employees Former ClientsFormer Clients

TrainingTraining Same as the undergrad studentsSame as the undergrad students

IASSIST 2005

The Other StudentThe Other Student(cont’d)(cont’d)

The Other StudentThe Other Student(cont’d)(cont’d)

What do they do?What do they do? Statistical Consulting for Undergrads, Statistical Consulting for Undergrads,

Grads, ProfsGrads, Profs Wide range of questions answered – from Wide range of questions answered – from

very basic (How do I Use SPSS?) to more very basic (How do I Use SPSS?) to more advanced (What is ANOVA?) to “Help, I advanced (What is ANOVA?) to “Help, I don’t know what I’m doing!”don’t know what I’m doing!”

They do Not do assignmentsThey do Not do assignments How is Consulting done?How is Consulting done?

1 hour appointments, booked in advance1 hour appointments, booked in advance The students can come alone or in groupsThe students can come alone or in groups

What do they do?What do they do? Statistical Consulting for Undergrads, Statistical Consulting for Undergrads,

Grads, ProfsGrads, Profs Wide range of questions answered – from Wide range of questions answered – from

very basic (How do I Use SPSS?) to more very basic (How do I Use SPSS?) to more advanced (What is ANOVA?) to “Help, I advanced (What is ANOVA?) to “Help, I don’t know what I’m doing!”don’t know what I’m doing!”

They do Not do assignmentsThey do Not do assignments How is Consulting done?How is Consulting done?

1 hour appointments, booked in advance1 hour appointments, booked in advance The students can come alone or in groupsThe students can come alone or in groups

IASSIST 2005

Benefits of Hiring Benefits of Hiring StudentsStudents

Benefits of Hiring Benefits of Hiring StudentsStudents

For themFor them On-campus job with flexible scheduleOn-campus job with flexible schedule Not stressful or physically Not stressful or physically

demandingdemanding Increases their knowledge of Increases their knowledge of

computer programs computer programs Increases their knowledge of StatsIncreases their knowledge of Stats Gives them valuable skills to be used Gives them valuable skills to be used

in the job marketin the job market A wonderful place to work!A wonderful place to work!

For themFor them On-campus job with flexible scheduleOn-campus job with flexible schedule Not stressful or physically Not stressful or physically

demandingdemanding Increases their knowledge of Increases their knowledge of

computer programs computer programs Increases their knowledge of StatsIncreases their knowledge of Stats Gives them valuable skills to be used Gives them valuable skills to be used

in the job marketin the job market A wonderful place to work!A wonderful place to work!

IASSIST 2005

Benefits of Hiring Benefits of Hiring StudentsStudents

(cont’d)(cont’d)

Benefits of Hiring Benefits of Hiring StudentsStudents

(cont’d)(cont’d)

For usFor us An investment in the future of the An investment in the future of the

Data CentreData Centre Allows the Data Centre to serve more Allows the Data Centre to serve more

clientsclients Allows us to increase our holdings Allows us to increase our holdings

because of the work the students do because of the work the students do on the datasetson the datasets

Allows the Data Centre to be open a Allows the Data Centre to be open a 40 hour week – even when the Full-40 hour week – even when the Full-time staff are awaytime staff are away

For usFor us An investment in the future of the An investment in the future of the

Data CentreData Centre Allows the Data Centre to serve more Allows the Data Centre to serve more

clientsclients Allows us to increase our holdings Allows us to increase our holdings

because of the work the students do because of the work the students do on the datasetson the datasets

Allows the Data Centre to be open a Allows the Data Centre to be open a 40 hour week – even when the Full-40 hour week – even when the Full-time staff are awaytime staff are away

IASSIST 2005

Drawbacks of Hiring Drawbacks of Hiring StudentsStudents

Drawbacks of Hiring Drawbacks of Hiring StudentsStudents

For themFor them lack of excitementlack of excitement very quiet, especially in the very quiet, especially in the

summersummer

For usFor us a Very big time investment - the a Very big time investment - the

training is training is VeryVery time consuming time consuming

For themFor them lack of excitementlack of excitement very quiet, especially in the very quiet, especially in the

summersummer

For usFor us a Very big time investment - the a Very big time investment - the

training is training is VeryVery time consuming time consuming

IASSIST 2005

Payoff of Hiring Payoff of Hiring StudentsStudents

Payoff of Hiring Payoff of Hiring StudentsStudents

Helps to meet the future Helps to meet the future demand for Data Professionals demand for Data Professionals In Data CentresIn Data Centres In the WorkplaceIn the Workplace

o A number of our former students are A number of our former students are currently in a job for which we have currently in a job for which we have trained themtrained them

Helps to meet the future Helps to meet the future demand for Data Professionals demand for Data Professionals In Data CentresIn Data Centres In the WorkplaceIn the Workplace

o A number of our former students are A number of our former students are currently in a job for which we have currently in a job for which we have trained themtrained them

IASSIST 2005

In Summary …In Summary …In Summary …In Summary …

Meeting the demand for Data Meeting the demand for Data professionals is an ongoing process. professionals is an ongoing process.

There are ways to meet the There are ways to meet the demand, such as:demand, such as: Holding Train-the Trainer sessionsHolding Train-the Trainer sessions Training students at the Training students at the

Undergraduate levelUndergraduate level

Meeting the demand for Data Meeting the demand for Data professionals is an ongoing process. professionals is an ongoing process.

There are ways to meet the There are ways to meet the demand, such as:demand, such as: Holding Train-the Trainer sessionsHolding Train-the Trainer sessions Training students at the Training students at the

Undergraduate levelUndergraduate level

IASSIST 2005

Thank you very muchThank you very muchThank you very muchThank you very much

Jane Fry, jfry@ccs.carleton.caJane Fry, jfry@ccs.carleton.caCarleton University, OttawaCarleton University, Ottawa

Ernie Boyko, Ernie Boyko, boykern@yahoo.comboykern@yahoo.comNesstar Americas, Retired Statistics Nesstar Americas, Retired Statistics

Canada,Canada,

OttawaOttawa

Jane Fry, jfry@ccs.carleton.caJane Fry, jfry@ccs.carleton.caCarleton University, OttawaCarleton University, Ottawa

Ernie Boyko, Ernie Boyko, boykern@yahoo.comboykern@yahoo.comNesstar Americas, Retired Statistics Nesstar Americas, Retired Statistics

Canada,Canada,

OttawaOttawa

IASSIST 2005