1. UBC IT Integrated Reporting Governance Committee June 13 th, 2011

2.  Introductions (10 min, Ian Burgess)  UBC IT Governance Update (10 min, Oliver Gruter-Andrew)  Terms of Reference (30 min, David Truong)  Confirm Terms of Reference  Confirm IR Governance Committee membership  Program Overview (30 min, David Truong)  Background  Conceptual Solution  Integrated Reporting Roadmap (draft)  Next Steps (10 min, David Truong) Agenda

3. Introductions  Name  Role at UBC  Familiarity with Reporting/Analytics and Data Management  Expectations for the IR Program

4. UBC IT Governance Update

5. Terms of Reference  Refer to Word document handout:

6. Program Overview: Background  Multiple departmental BI solutions  Varied landscape of licensed tools including Oracle, IBM, MSFT, SAP, Jaspersoft, MSTR, SPSS, Custom, Open Source  Spaghetti of interconnections for data integration with many point to point interfaces that are manual, incomplete, and of uncertain quality  Early “Data Warehouses” in PAIR and in Enrolment Services  Critical stakeholder needs not fully met for integrated information and query/reporting access  Data governance is distributed  Data Model and Dictionary lacking or non-existent in some areas Based on the current state of reporting and data management solutions at UBC, there is significant benefits that can be gained through a central IR platform.

7. Program Overview: Conceptual Solution (1 of 5) The program will seek to establish a standard information management framework to service the broader University community. Data Access Data ManagementData Integration Governance Data Security Data Sources Metadata Operations

8. Program Overview: Conceptual Solution (2 of 5) Data Access Data Management Governance Data Security Metadata Operations Data Integration Data Sources Data Quality Extract, Transform, Load Data Enrichment Batch Near Real-time Cleansing Profiling Harmonization Demographic Lineage Etc. The Data Integration layer will extract key operational data, apply transformation logic, cleanse and conforming the data; typically 60% to 80% of effort spent here. Finance Student HR External Research Land & Building Academic

9. Program Overview: Conceptual Solution (3 of 5) Data Access Governance Data Security Metadata Operations Data Management Data Warehouse Atomic Data Warehouse Subject Specific Data Marts Source Data Sets Unstructured Information Master Data Operational Data Store Business Views Enterprise Data Warehouse Data Integration Data Sources Data Quality Extract, Transform, Load Data Enrichment Batch Near Real-time Cleansing Profiling Harmonization Demographic Lineage Etc. The Data Management layer contains the different data stores of operational and enriched data; key here is properly documented data model and dictionaries. Finance Student HR External Research Land & Building Academic

10. Program Overview: Conceptual Solution (4 of 5) Governance Data Security Metadata Operations Data Access Reporting / Analysis Data Mining Ad-hoc Analysis Reports Enterprise Portal Dashboards Publish / Alerts Mobile Performance Management Data Management Data Warehouse Atomic Data Warehouse Subject Specific Data Marts Source Data Sets Unstructured Information Master Data Operational Data Store Business Views Enterprise Data Warehouse Data Integration Data Sources Data Quality Extract, Transform, Load Data Enrichment Batch Near Real-time Cleansing Profiling Harmonization Demographic Lineage Etc. The Data Access layer is where the various information delivery channels are used depending on the type of analysis being done. Finance Student HR External Research Land & Building Academic

11. Program Overview: Conceptual Solution (5 of 5) Governance Metadata Methodology Technical Business Strategy/Vision Demand Planning Capability Definition Release Management StandardsSkills/Training Metadata Data Security Data Privacy Authentication Authorization Operations AuditError-Handling Data Retention Single Sign-on ID & Access Mgmt Capacity Schedule Backup/ArchivePerformance Data Access Reporting / Analysis Data Mining Ad-hoc Analysis Reports Enterprise Portal Dashboards Publish / Alerts Mobile Performance Management Data Management Data Warehouse Atomic Data Warehouse Subject Specific Data Marts Source Data Sets Unstructured Information Master Data Operational Data Store Business Views Enterprise Data Warehouse Data Integration Data Sources Data Quality Extract, Transform, Load Data Enrichment Finance Batch Near Real-time Student HR External Research Land & Building Cleansing Profiling Harmonization Demographic Lineage Etc. Governance, Metadata, Security, and Operations provide important supporting processes. Academic

12. Roadmap (1 of 4) The IR Roadmap provides a blueprint to achieve the desired target state over the next 5 years.

13. Roadmap (2 of 4) Initial focus is to mobilize the program and understanding the Oracle BI packaged solution.

14. Roadmap (3 of 4) Finance & Procurement, Student, and PAIR have initially been identified as key areas of focus.

15. Roadmap (4 of 4) The program will focus on growing the maturity of reporting/analytics and enterprise data management.

16. Next Steps  Continue to mobilize the program  Evolve and confirm the roadmap  Establish the Program Organization including the working committee  Train key resources  Establish the Oracle BI Environment  Install and demo the Oracle BI solution  Identify a meaningful proof of concept  Confirm the scope of work against the approved budget  Identify quick win initiative(s) to begin leveraging Oracle BI platform Over the next couple of months, the program will focus on: