Data Warehouse Leadership Team

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Data Warehouse Leadership Team :: Meeting Notes and Handouts, May 15, 2013

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Leadership Team Member Representing In Attendance
Joyce Lopes Vice President, Administrative Affairs X
Volga Koval Academic Affairs Data Expert X
Dale Sanford Student Affairs Data Expert X
Amber Blakeslee Administrative Affairs Data Expert X
Sandra Joubert-Amiel University Advancement Data Expert  
Denise Giltzow Human Resources X
Melissa Koval Academic Personnel Services X
Jacqueline Honda Institutional Research X
Anna Kircher Chief Information Officer X
Staff to the Leadership Team Representing  
Ronda Stemach Systems Analyst, Enterprise Data Management X
Ward Headstrom Systems Analyst, Institutional Research  
Josh Callahan Director, Enterprise Technology X
Additional Participants Representing  
Teal Sexton University Budget Office X
John Filce Institutional Research X
Phil Rouse Process Improvement X
Travis Williams Advancement X


Agenda Topics and Meeting Summary

1. Strategies for Constructive Team Dialog

  • Lanaya presented a “Fierce: Conversations” PowerPoint, with a focus on understanding and incorporating different perspectives in team conversations and decision-making.
  • Handouts: PowerPoint slides, Beach Ball Preparation Form.

2. Review SWOT Survey Results

The team discussed SWOT results from the last meeting.

  • Strength: Good customer service.
  • Weaknesses: Many separate data sources, not enough human resources.
  • Opportunities/Threats: Misuse of data results in organizational confusion, but creates the opportunity for streamlining/centralizing data and improving communication across organizational areas.

Key issues/themes:

  • Disparate data. It is important to educate employees about what kind of data is available and where it can be found. Improvements to PeopleSoft and OBI may help to eliminate the widespread dependence on separate shadow systems. 
  • Employee wants/needs. What kind of tools and trainings are needed for employees to be able to efficiently and effectively use available data? For example: how to find and understand trend data, build appropriate reports, connect local databases to OBI/PeopleSoft, etc.
  • Common Definitions. Basics of data organization and definitions of data should be clearly defined and in place before moving on to tackle more technically-oriented themes. For instance, ‘predictive analytics’ has many meanings and implications across different business areas.

3. Action Item

  • Each team member will use the Beach Ball Preparation form to identify their top two issues, and e-mail Joyce & Melanie with their results.
  • The team will consider whether all the right people have been included in the Data Warehouse Leadership meetings; are there others who ought to be included?