1. HIGHER ED DATA VISUALIZATION USING TABLEAU Kenneth M. Brown Whitworth University July 14, 2016 Analytics and Reporting Forest Grove, Oregon NWEUG 2016

2. SESSION RULES OF ETIQUETTE  Please turn off your cell phone/pager  If you must leave the session early, please do so as discreetly as possible  Please avoid side conversation during the session Thank you for your cooperation!

3. INTRODUCTION  Explore data analysis and visualization examples and applications in direct support of Admissions, Institutional Advancement, Retention and Business Office and Departmental budgeting and budget analysis. Will highlight the effective use of Tableau to aid daily departmental operations as well as in support of Strategic Planning, Institutional Research and Institutional Effectiveness.  Gain insight into what the use of Tableau can bring to your institution along with how it can integrate into your operational environment.

4. SESSION AGENDA 1. Introduction to data analytics, visualization and data informed decision making 2. Whitworth’s systems and analytics environment 3. Examples of data analytics at Whitworth 4. Demonstrations 5. Question?

5. INTRODUCTION TO DATA ANALYTICS The use of data analytics and visualization as part of a continuum of business intelligence capabilities to enable data informed analysis and decision making.

6. INTRODUCTION TO DATA ANALYTICS  Business Intelligence as a Continuum  Descriptive : Informing and creating awareness of what happened  Diagnostic : Analyzing and Experimentation to understand why it happened  Predictive : Determining what will happen  Prescriptive : What actions can we take to make it happen

7. INTRODUCTION TO DATA ANALYTICS  A few of the areas that we are directly supporting through analytics and visualization  Strategic Planning : Informing and tracking progress towards goals  Admissions : Goal setting, territory management forecasting, tracking progress, understanding trends, testing hypothesis, funnel management  Advancement : Campaign support and modeling, list management, predictive modeling, tracking, reporting  Business Office : Student accounts payable management, budget development and modeling, revenue and expense attribution and forecasting  Academic Affairs : Program costs, course/section planning and management, student/course performance, retention alerting, modeling and projecting,  Student and Residence Life : Dorm and board tracking, planning, student activities, student support services  Institutional Research : Fact Books, university metrics and reporting, planning and analysis, survey analysis, data preparation for upload

8. WHITWORTH’S SYSTEMS AND ANALYTICS ENVIRONMENT

9.  Primary Applications in use  Ellucian Colleague ERP for GL, BO, HR, Payroll, A/P, Student, Registrar, Advancement, etc. (UNIX, UniData)  Microsoft Dynamics based Enrollment Management system and SalesForce.com (soon to be replaced by Slate)  Blackboard  Qualtrics  Data repositories and data sets  MS SQL based Data Warehouse (nightly extracts from ERP, Enrollment Management)  Text,.csv and.xlsx extract files  MS SQL Server databases  Reporting and analytics tools  Informer  Tableau  Alteryx

10. DATA FLOWS Colleague Informer Data Warehouse Text,.csv files Reports Excel Extracts Tableau Models Dashboards What if’s Dynamics and Slate Alteryx Qualtrics

11. EXAMPLES OF DATA ANALYTICS AT WHITWORTH

12. What Happened

14. What’s Happening

15. What

16. What Happened and Where

17. What’s Happening

18. What Happened

19. Why and What Might

20. What/Is

21. What Might Happen

22. DEMONSTRATION

23.  Visualization Basics and Orientation  Data Connections  Chart Types  Calculations  Dashboards  Publishing

24. QUESTIONS & ANSWERS

25. THANK YOU! Ken Brown kbrown@whitworth.edu