UBC IT

Integrated Reporting Governance Committee

May 1st, 2012

Action Items from last meeting: Update on ISI Recruitment & Admission request Clarification on Budget functionality

Program Status

Data Governance:  Data Governance Defined IAM, IR, & Person Master Data Management

Agenda

Working committee recommended that option 3 to bring Admission data into Foundation R1 in FY12/13

Value seen in bringing Admission forward

Estimated that additional $253K required to bring Admission scope forward

Update on ISI Recruitment & Admission request:

Option 1: Focus on Student Revenue AnalyticsPros: -supports faculty funding model and integration between student & finance-aligns to current scope and budget

Cons:-does not provide meaningful core data to ISI

Student Biographical

Admissions

RecruitmentStudent Financials

Student Records & Registration

Student Biographical

Admissions

Student Financials

Student Records & Registration

Student Biographical

Admissions

RecruitmentStudent Financials

Student Records & Registration

RecruitmentOption 2: Focus on ISI AnalyticsPros:-addresses entire core data needs of ISI

Cons:-departmental BI solution (no integration with non-student data)-additional funding required for increased scope

Option 3: Student Revenue Analytics with partial ISIPros: -achieves student revenue analytics and “integrated” reporting-provides core admission data for ISI

Cons:-additional funding is required to take on increased scope

Budget data (e.g. ) from FMS will be integrated into the DW as part of Foundation R1 with the exception of Plan and Forecast data from Hyperion/Essbase is planned for Foundation R2 (FY13/14).

Further analysis around the right Budget & Planning reporting solution (Hyperion vs. OBIEE, user acceptance, change management, etc) needs to be further assessed in Foundation R2.

Cost/Benefit to bring in and report on planning in OBIEE, as it is usually out of date very shortly into the business cycle as the campus reflect their changes in the forecasts.

Funding for Budget functionality will be covered under $5M Comptroller large project funding.

Update on Budget Functionality:

Action Items from last meeting: Update on ISI Recruitment & Admission request Clarification on Budget functionality

Program Status

Data Governance:  Data Governance Defined IAM, IR, & Person Master Data Management

Agenda

Program Status

Previous Status

Current Status

Explanation

Scope Green Yellow -Request from ISI to include Admission Schedule Yellow Green -Completed Discovery activities including high

level scope -Initiated Student and Finance foundation detailed requirements definition

Resources Yellow Yellow -Assessing potential resource gap due to increased Admission and Recruitment data scope -Continue to monitor and balance operational commitments of resources

Budget Green Green

-Program budget reviewed with Governance committee -Admission source of funding currently being identified

Program Schedule

Data Governance

May Jul Aug Sept Oct Dec Jan-2013 Nov

Governance Committee

Finance Foundation Development

Quality Assurance

Define QA Approach Finance SIT Preparation

Student SIT Preparation

Finance UAT Preparation

Technical Architecture

Plan & Analyze

Setup Finance DEV Setup PROD

Environment Support

Change Management 1

INFA & OBIEE Training

Prepare Train-Trainer Materials (Finance)

Train-Trainer

Today

Feb

Finance BRD Sol’n Blueprint

Updated WBS Updated

JunApr Mar

Design/Build/Test GL Dashboards Execute SIT Execute UAT

Execute Performance Test

Mar-2012

Plan & Analyze

SIT Test Results

Test Summary Sign-off

UAT Test Results Test Summary Sign-off Deployment to core

Financial Users

ORT completed Deployment to Broad

Financial users

Design/Build /Test Records & Registration

Student Foundation Development

Student BRD Sol’n Blueprint

Updated WBS Updated

Design/Build/Test Student BIO Design/Build/Test SFM Execute UAT

Execute Performance Test

Deploy

Go Live #3

Plan & Analyze

ETL Data Mapping Logical Data Model

Updated Report mock-ups Sol’n Blueprint Updated QA Test Plan

ETL Code DW DDL OBIEE Code Unit Test Results SIT Test Plan

Updated

SIT Test Results

Test Summary Sign-off

UAT Test Results

Test Summary Sign-off

ORT completed

Deploy to all users

QA Approach

Deploy 2

Go-Live #2

Design Common Components

Build/Prototype Common Components

Setup Student DEV

Setup Finance SIT Setup Finance UAT & PERF

Setup Student SIT

Test Plan & Scripts Expected Results

Plan & Prepare Performance Test

Plan & Prepare Performance Test

Test Plan & Scripts Expected Results

Student UAT Preparation

Test Plan & Scripts Expected Results

Test Plan & Scripts Expected Results

Change Mgmt Approach

Program Communication

Perf Results & Stress Baseline

Perf Results & Stress Baseline

Support End-User Training Prepare Train-Trainer Materials (Student)

Train-Trainer

Support End-User Training

Setup Student UAT & PERF

Test Plan & Scripts Test Plan & Scripts

Tech Arch diagrams

Tech Arch diagrams

Regression SIT

ETL Code DW DDL OBIEE Code Unit Test Results SIT Test Plan

Updated

Design/Build /Test Admission

Design/Build/TestAP & PO Dashboards

ETL Code DW DDL OBIEE Code Unit Test Results SIT Test Plan

Updated

HR/PayrollChartfield Lookup

Deploy 1

Go-Live #1

Working Committee

Action Items from last meeting: Update on ISI Recruitment & Admission request Clarification on Budget functionality

Program Status

Data Governance:  Data Governance Defined IAM, IR, & Person Master Data Management

Agenda

9

Data Governance enables an enterprise to manage its data assets. It includes the rules, policies, procedures, roles and responsibilities that guide overall management of an enterprise’s data. IR Data Governance provides the guidance to ensure that data is accurate and consistent, complete, available, and secure. This enables data to be more efficiently and effectively turned into business insight.

IT Governance IT is the pipes that move the information (pumps, filters, tanks, switches, etc.)

IT Governance are decisions about the pipes (pumps, filters, tanks and switches).

IR Data Governance Data is the liquid that is flowing through the pipesIR Governance directs decisions about the data; the liquid flowing through the IT systems (pipes)

PeoplePeople

ProcessProcess TechnologyTechnology

IT vs. Data Governance

Data Governance Data Governance is how an enterprise manages its data assets. Governance includes the rules, policies, procedures, roles and responsibilities that guide overall management of an enterprise’s data. Governance provides the guidance to ensure that data is accurate & consistent, complete, available, and secure. This enables data to be more efficiently and effectively turned into business insight.

Data Stewardship

Data Stewardship is the accountability for the management of data assets. Data Stewards do not own the data; instead they are the caretakers of the enterprise data assets. The Data Stewards ensure the quality, accuracy and security of the data.

Data Ownership Data Ownership is the responsibility for the creation of the data, and the enforcement of enterprise business rules. Data Owners (Business SMEs) usually refers to the business owners of Master/Business Data.

Data Policies Data Policies are the high-level and/or detailed rules and procedures that an enterprise utilizes to manage its data assets. Data Policies might include adherence of data to business rules, enforcing authentication and access rights to data, compliance with laws and regulations, and protection of data assets.

Data Standards Data Standards are the precise criteria, specifications, and rules for the definition, creation, storage and usage of data within an organization. Data Standards include basic items like naming conventions, number of characters, and value ranges. Data Standards may also dictate specific quality measures, retention rules, and backup frequency.

Data Governance Defined

Business Units and Functional Areas operate with complete autonomy, while attempting to maintain global standards to meet specific enterprise requirements.

Federated Governance provides a single point of control at the enterprise level for decision making, as well as governance structures at the business unit level for decisions.

Centralized Governance provides a single point of control at the enterprise level for decision making, with business units & functional areas having little or no responsibility.

A range of options exist for data governance structures. At one extreme, decentralized models place all data decisions ‘locally’ or at the business unit or functional areas. At the other extreme all decisions are made centrally at the enterprise level. A hybrid, or federated model, puts some decisions at each level of the governance structure and supports broad representation.

Limited Success forEnterprise Data Governance

Effective forEnterprise Data Governance

Decision Making

Decentralized Federated Centralized

Data Governance Organization Options

Data StewardsData Stewards

Data ArchitectsData Architects

Data Owners(Business SMEs)

Data Owners(Business SMEs)

Database Administrators

Database Administrators

• Resolve data integration issues

• Determine data security

• Document data definitions, calculations and summarizations

• Maintain/update business rules

• Analyze and improve data quality

• Define mandatory data elements that need to be measured

• Define and review metrics for measuring data quality

• Translate Business Rules into Data Models

• Maintain Conceptual, Logical and Physical Data Models

• Assist in Data Integration Resolution

• Maintain Metadata Repository

• Generate Physical Database Schema

• Performance Database Tuning

• Create Database Backups

• Plan for Database Capacity

• Implement Data Security Requirements

Senior Executive Sponsorship

Senior Executive Sponsorship

• Provide campus wide governance to strategic decisions impacting the IR DW such as new subject areas, new data sources, new business problems solved with the DW

• Business Data Owner

• Understand data

• Define rules

• Identify errors

• Set thresholds for acceptable levels of data quality

Change ManagementChange Management

• Provide education on the importance of data quality to the company

• Communicate data quality improvements to all employees

Data Management LeadData Management Lead

• Oversee the organizations’ data stewardship, data administration and data quality programs

Proposed Model for IR Program

Governance CommitteeWorking Committee

Data Governance & Person Master Data

As we move in the Foundation phase of the program, we will need the IR Working and Governance committees to discuss governance of master data that are in the scope.

On IR, Student Biographical data is one of the first building blocks of Student Foundation R1; in the future other aspects of person including instructors, employee, alumni, donor, researcher will need to be considered.

IR and IAM Programs having been working together to determine how to leverage the Identity map created by IAM, and structure a solution to address Person MDM.

IAM Program Scope“Work with HR, IT, Student Information Management, Compliance, and Security to deliver Authentication, Authorization, Identity Management, Auditing, and User Lifecycle Management, and to Students, Employees, Faculty, Prospective Students, Retirees, Alumni, and Guests to provide the right access to the right information for the right people at the right time.”

Scope of AssessmentAnalyzed 8 IAM processes during 16 sessions…

On-boarding Termination Authentication Authorization Group Management Identity Data Management Password Self-service Access Recertification

For 7 User Types…

Students Employees Faculty Prospective Students Retirees Alumni Guests

Reviewed existing identity sources and 13 mission-critical administrative applications…

ACMS Ad Astra Archibus FMS HRMS Key Desk Library/EZ Proxy LMS/CT Connect SEoT SIS UBCcard UBC Directory

IncreasedSecurity

IncreasedSecurity

OperationalEfficiency

OperationalEfficiency

ServiceEnablement

ServiceEnablement

Sustainably reduce university-wide costs by eliminating duplication and waste. Invest in engineering efficient processes and implementing cost-saving technologies. Optimize IAM organization and leverage strategic partners for non-core capabilities.

Enhance end user (students, faculty/staff, alumni, etc.) experience in getting the appropriate access they require in a timely and seamless manner to allow fast, secure access to mission-critical administrative systems.

Adopt appropriate balance of technology, processes and procedures to mitigate internal and external threats, particularly to prevent fraud and sensitive data loss. Increase visibility on users’ access (i.e. “who has access to what” and “who should have access to what”), in adherence with industry best practices

IAM Program Drivers

Identity Map

Phase 1 of Identity Management:

1.List Systems that should be connected to IdM 2.Detail data flows between connected systems3.Agreement on identity attributes and processes the Identity Management Systems will take responsibility for managing4.Establish the “gold source” for each identity attribute

1. HRMS and SIS are the Systems of Record for Active Faculty, Staff and Students

2. All of the core administrative systems collect and store identity attribute data about people and create accounts

3. HRMS and SIS receive Identity attribute data from applicants via ISIS, EZRecruit and PASBC using both paper and on-line processes.

4. There are 134 identity attributes in the 13 core admin systems5. Recommendation: IAM systems manage/deliver 7 identity

attributes (gold source for CWL login, password and PUID)

HRHROTHEROTHER

SIS

Identity Map Results

IAM Program External Dependencies