Copyright 2007, Information Builders. Slide 1 The Relevance of Data Governance in Higher Education Tim Beckett Higher Education Solutions November 9, 2011

Agenda  Welcome & introduction – Tim Beckett  Part I – Panel Discussion  Part II – Presentation  Q&A Copyright 2007, Information Builders. Slide 2

Introduction  Getting serious about the mission  Questions are being asked  By the government  By the Ministry  By the state  By donors  By executives  By accreditation bodies  “It depends…” Copyright 2007, Information Builders. Slide 3

Part I  Panel Discussion  Data Governance at Three Higher Education Institutions  Moderated by Dan Schultz, Director, iWay Software  Peter Webb, Institutional Research, University of the Fraser Valley (British Columbia)  Mark Horseman, Data Administration Analyst, University of Saskatchewan  Linda Pennington, Information Technology Services, San Jacinto College (Texas) Copyright 2007, Information Builders. Slide 4

Dan Schultz Director, iWay Software November 9, 2011 Data Governance in Higher Education

Fundamental Requirements for Success Copyright 2007, Information Builders. Slide 6

Creating the Environment to Succeed Most fundamental requirements  Data Integration  Maximize availability of data assets  Data Governance  Create, implement, and maintain data policy  Data Quality  Optimize information asset integrity  Data Synchronization  Link and manage complex data relationships  Business Intelligence  Real-time decision making based on the right information  Guiding Methodology  Best practice approach Copyright 2007, Information Builders. Slide 7 Technology & business process working together

Information Builders Enterprise Information Management (EIM) Framework Creating and Supporting a Data Governance Initiative Copyright 2007, Information Builders. Slide 8

Business Process IB Enterprise Information Management Framework Data Quality Data Governance Business Intelligence (Analytics/Operations) Business Intelligence (Analytics/Operations) System, Data, & Intellectual Fragmentation (Costly Business & Technical Problems) System, Data, & Intellectual Fragmentation (Costly Business & Technical Problems) Single View (MDM) Single View (MDM) Strategy Roadmap Education Implementation Mentor Advocacy Best Practices Experience Profile Cleanse Match Remediate Data Access Data Movement Consulting Data Policy Standards Business Rules Roles & Responsibilities Stewardship Data Ownership Data Integration Technology

Data Integration Maximizing the Availability of Information Assets A fundamental requirement to the success of a Data Governance Initiative Copyright 2007, Information Builders. Slide 10

Data Integration Copyright 2007, Information Builders. Slide 11 Maximizing availability of Information Assets

Data Quality Optimizing Information Asset Integrity A fundamental requirement to the success of a Data Governance Initiative Copyright 2007, Information Builders. Slide 12

1. Profiling: Investigation into data - Analysis of data to provide insight into the quality of the data and aid in the identification of data quality issues. 2. Parsing, standardization, & Cleansing: Decomposition of fields into component parts and formatting of values into consistent layouts based on industry standards, local standards, user-defined business rules and knowledge bases of values and patterns. Modification of data values to meet domain restrictions, integrity constraints or other business rules that define sufficient data quality for the organization. 3. Enrichment - add contextual or complete the data. Geographical data, increase the data information for entities. 4. Monitoring: Deployment of controls to ensure ongoing conformance of data to business rules that define data quality for the organization. Components of Data Quality Technology Data Quality – Automated tools for optimizing information integrity

Data Governance Creating, implementing, and maintaining data policy A fundamental requirement to the success of a Data Governance Initiative Copyright 2007, Information Builders. Slide 14

Data Governance – Fundamental Concepts Technology or business process? It requires an element of both to be successful. Business process allows the institution to coordinate, establish, and oversee institutional data policies and practices. Technology allows for the implementation and automation of data policies established through the data governance business process.

Business Process Data Governance within the IB EIM Framework Data Quality Data Governance Business Intelligence (Analytics/Operations) Business Intelligence (Analytics/Operations) System, Data, & Intellectual Fragmentation (Costly Business & Technical Problems) System, Data, & Intellectual Fragmentation (Costly Business & Technical Problems) Single View (MDM) Single View (MDM) Strategy Roadmap Education Implementation Mentor Advocacy Best Practices Experience Profile Cleanse Match Remediate Data Access Data Movement Consulting Data Policy Standards Business Rules Roles & Responsibilities Stewardship Data Ownership Data Integration Technology DG enabled technology Business rule based Work flow enabled

Single View of the Citizen Copyright 2007, Information Builders. Slide 17 Data remediation work flow for the data exceptions

Single View of the Citizen Data Synchronization Link and manage complex data relationships A fundamental requirement to the success of a Data Governance Initiative Copyright 2007, Information Builders. Slide 18

Convert to a “Single View” Based Culture Copyright 2007, Information Builders. Slide 19  Master Data are the facts describing your core business entities: Students, faculty, classes, facilities, chart of accounts, location and employees. It is the high value information an organization uses repeatedly across many business processes.  Single View technology decouples master information from individual applications and ensures consistent master information across transactional and analytical systems  Single View solutions are software products that:  Support the global identification, linking and synchronization of customer information across heterogeneous data sources  Create and manage a central repository or a database- based system of record  Enable the delivery of a single view for all stakeholders  An Single View program potentially encompasses the management of student, asset, person or party, supplier and financial masters.

Questions?

Next Step Opportunities  Speak to Information Builders about  Institutional Intelligence and/or  Enterprise Information Management  Please give us your feedback (evaluation form)  Tim Beckett Information Builders Higher Ed / K-12 Solutions Manager Direct: Copyright 2007, Information Builders. Slide 21

Copyright 2007, Information Builders. Slide 22