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UM Data Deep Dive IUG Presentation June 2011

UM Data Deep Dive

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UM Data Deep Dive. IUG Presentation June 2011. UM Background. Multiple data sources Datacom mainframe Locally developed applications Optix documents Sheets of paper Minimal documentation Dispersed knowledge among functional users Single point of technical knowledge - PowerPoint PPT Presentation

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Page 1: UM Data Deep Dive

UM Data Deep DiveIUG PresentationJune 2011

Page 2: UM Data Deep Dive

UM Background

Multiple data sources• Datacom mainframe• Locally developed applications• Optix documents• Sheets of paper

Minimal documentation• Dispersed knowledge among functional users• Single point of technical knowledge

No single unit responsible for ETL

Page 3: UM Data Deep Dive

UM Priorities

Document what we currently have• Identify “dirty” data• Clarify areas where multiple concepts are

interwoven in a single data point Understand where current data elements fit

within Kuali Student• Identify gaps in KS• Identify areas for manual data entry

Have it done yesterday

Page 4: UM Data Deep Dive

UM’s Strategy Weekly sessions with homework

• Difficult to get momentum, maintain focus• Homework doesn’t get done• No distinction between what is needed now and later

“Deep Dive” Approach• Day-long workshop - Food• Focus on a single source/table• Prioritize activity• Assign jobs including notetaker

Finish with “Data Mapping Smackdown”

Page 5: UM Data Deep Dive

Guiding Questions

1. Is this the primary source of this information?2. Is this the ONLY source of the information?3. What is the “shelf life” of this information – how

long is it useful?4. Who “owns” the information – i.e., who can

make changes to it?5. Why do we need this information – what

decisions does it support, questions does it answer, etc.?

Page 6: UM Data Deep Dive

Sample Agenda

Introduction (5 minutes) and Assignments Identify Important Data Elements

• What elements specifically relate to the Curriculum Management functionality?

• Cursory discussion leading to initial list of elements Build out data documentation for each element. Create an action list for follow up.

Page 7: UM Data Deep Dive

Work Products

Data sources brainstorming spreadsheet

Combined sources documentation and mapping sheet

Page 8: UM Data Deep Dive

Results Most curricular data sources are documented

• Found additional sources along the way• Changed priorities• Identified pain points – shaped implementation

strategy Focused mapping on initial implementation –

course proposal process Identified areas for manual data entry

• Course & program rules• ECON learning objectives & categories

Page 9: UM Data Deep Dive

Next Steps

Identify ETL resources Make decisions around pain points

• Old proposals – how best to deal with Optix• Special topics courses• “Curricular” decisions outside of course/program

approval• Additional CLU types not currently exposed –

exam, project, experiental learning