1. SAKAI and ANALYTICS A Case for collaboration in Analytics Space 2011 Sakai conference Los Angeles 1

2. Analytics for ATLAS Advanced Teaching, Learning and Scholarship  Where are we today  What are the possibilities  Low hanging fruits  Where do we want to be  How do we get there 2 2

3. Maturity Model Predictive Modeling Time Line Maturity Growth Infancy Querying and Reporting Scorecards and Dashboards 3 Sage

4. Data, Data, Data  All the data are available already  Data Acquisition  Data Transformation  Data Richness 4

5. Life Cycle Reporting 5 Courses and Classes Grades Development goals Donor Information State Grants Federal Loans School & Personal Information Aptitude Data Admissions Financial Aid RegistrarAlumni

6. Need for Business Intelligence  Data  Information  Knowledge  Actionable Knowledge  Strategic Recruiting  Advising  Intervention  Student Retention 6

7. Consumers of Information  Students  Faculty  Technologists Traction  Direction  Exploration 7

8. Usage Data  Participant Logins  Participant Summary  Page Hits 8

9. Portfolio Activities  Portfolio Data  Types of Content  Most accessed  Participant Activity 9

10.  Indicative Data from SIS  Admissions Data  Alumni Data 10 Data Richness 10

11. External Tagging  Aggregate Data from “Services”  “Recommend” Service  Assessment Matrices 11

12. 12

13. Institutional Key Performance Indicators  Qualitative Program Assessment  Multiple Entry Points  Gauging Student Engagements  Rolling Course Evaluation  Quantify Teaching Credentials  Retrospective Evaluation  Advisor Evaluation 13

14. Continued…  Cross Institutional Analysis  Co-curricular Activities  Student Life 14

15. 15 Pentaho BI Oracle OBIEE NYU BI Tools 15

16. 16 Contact Information Lucy Appert Director of Educational Technology, Liberal Studies Program lucy.appert@nyu.edu Madan Dorairaj, PM dorairaj@nyu.edu 16