Data Warehousing: Changing Campus Culture

Copyright 2005 Ora Fish RPI

Data Warehousing: Changing Campus Culture

Ora Fish, Data Warehouse Program Manager

Rensselaer Polytechnic Institute


Rensselaer Polytechnic Institute (RPI)

“We are the first degree granting technological university in the English-speaking world”

Research University with programs in Architecture, Arts, Engineering, Humanities, Science, and Social Sciences Rensselaer enrolls over 7,500 undergraduates, graduate, and working professionals.

Over 450 Rensselaer faculty members include National Science Foundation Presidential Faculty Fellows, members of the National Academy of Engineering, the National Academy of Sciences, and other eminent professional organizations.

Founded in 1824 by Stephen Van Rensselaer


Fundamental Problem

Operational systems are not designed for information retrieval and analytical processing


History of DW at Rensselaer Fall 1998- Summer 2001: Looking for solution Fall 2001: Budgets are approved Fall 2001 - Jan 2002: Building infrastructure Jan 2002 – today: Delivering Enterprise Wide Warehouse

with the following areas: Finance Positions Human Resources Student Enrollment Admissions Graduate Financial Aid Undergraduate Financial Aid Research (pre award, post award) Institute Advancement (in progress)


Data Warehouse group

Part of the Administrative Computing within the Division of Chief Information Office

Total of eight employees Responsible for addressing campus

reporting and analytical needs http://www.rpi.edu/datawarehouse/

http://www.rpi.edu/datawarehouse/

http://www.rpi.edu/datawarehouse/


Our constituency

Administrative leadership: President, VP of Finance, VP of Student Life, Provost, Dean for Graduate Admissions, Controller, Registrar, Dean of Enrollment, VP of Research, AVP of Budgets, etc.

Academic leadership: Deans and Department Chairpersons, Research Center Directors

Core Administration: Institutional Researcher, Director of Budgets, Director of Enrollment, Registrar, Director of Research Administration, etc.

Core Administration Personal: responsible for carrying out centralized functions such as registration, admissions, payroll, etc.

Campus Administrative Personal - Graduate Coordinator’s Assistant, Business managers across campus, Coaches, etc.

Faculty


Viewpoint

Regardless of how well designed our star schemas are or how well the dimensions are conformed, to be effective in addressing campus decision support and analytical needs the Data Warehouse should be viewed as a service addressing information quality and campus culture


Viewpoint

The true benefits can be achieved only when the new technology is adapted and becomes part of our business routine:

Penetration takes time Brings transformational changes to

Processes and Culture


Successful Data Warehouse implementation

Clear set of Goals and Objectives Sponsorship Budgeted Dedicated staff Strong alliance between IT and Business Implemented as a Service Proved implementation methodology Addresses Information Quality Serve as a catalyst for change


The Fundamental Goal

The fundamental goal of the Rensselaer Data Warehouse Initiative is to integrate administrative data into a consistent information resource that supports planning, forecasting, and decision-making processes at Rensselaer.


Data Warehouse Objectives

Serve as an information hub for Administration as well as the Academic Schools

Transform Data into Information with embedded business definitions

Informative - Meta Data Intuitive for end user to perform ad-hoc

queries and analysis Adequate response time - Retrieved within

seconds


Business Sponsorship

Lack of Business SponsorshipPrototype

Shop around and identify area where it ‘hurts’ Build a prototype and invite vendors to participate Market to the business side

Engage and build awareness Facilitate a visit to the peer institution Invite peer institution to your campus

Be aware of offering temporary solutions Costly in a long run Will have dissatisfied customers

Wait for leadership to change


Lack of IT Sponsorship

Typical reasons are: Lacking knowledge and/or expertise, Do not have necessary resources; Not enough demand or pressure from the top

Possible steps: Secure funding Bring in outside help with knowledge transfer Build Prototype as a joint venture Engage and Build awareness Emphasize partnership Engage Leadership (Business Sponsor) in

setting IT priorities


Budget

Budget is the true indication of sponsorship support and priority

Hardware and software for Production, Test, and Training environment

Data base servers Data base licenses ETL Front-end Personnel Education and travel Consulting services Contingency


Dedicated Staff

Need dedicated personnel to carry out the following functions Project Manager/Champion DBA Modeler ETL developers Front end developers Software administration and installation Desktop support Customer support Campus training Business staff and Power user


Alignment between the IT and the Business in DW implementation

Technology

Alignment

Business

CampusCulture

Information QualityArchitecture


Information Quality

Accurate, Reliable, Consistent, Relevant

Re-enforce common definitions Set up processes to identify and clean

erroneous data Set up processes to gather relevant data Define policies on who will have access

to what information


CultureFrom Transaction Processing Environment to Decision Support Environment

The goal is to build analytical culture that values and promotes usage of information in decision making


CultureFrom Transaction Processing Environment to Decision Support Environment

Promotes fact based decisions where value is placed on decisions made through usage of information vs. supply of data

Lowers the walls across organizational boundaries and promotes understanding of the business enterprise across different functional areas

Analytical culture requires different set of skills


Our Approach

The approach to addressing campus informational needs can not be:

A Project A Product

It is a service


Implementing Data Warehouse

Build Technical Architecture Establish Services in support of campus

community Build Processes ensuring Data Quality Work with campus Leadership on

addressing campus analytical culture


Methodology Addresses long term solution Enterprise wide integrated data warehouse vs.

Departmental data mart Use methodology with proven success i.e. learn from

others Overall long term planning with short time to delivery Has to include all aspects of DW implementation

Architecture addressing transformations, meta data, security, delivery

Campus rollout and training Information Quality Communication Support


Implementation Methodology

Build DW Foundation

DevelopSubject Oriented

Data Marts

Release Data Martto the Campus

Next Data MartRelease Data Mart

To the Core AdministrationData stewards

Maintenance and Support

Campus Communication

Continuing Adaptation and Growth……

Training


DataWarehouse

SourceDatabase

SourceDatabase

OtherSources

(e.g. files,spreadsheets)

ETL

DataMart

Data Cube

Web ClientInterfaces

ApplicationServers

OperationalData Store

DesktopInterfaces

• operational systems• transactional systems

• extraction• transformation• modeling• loading

• central repository• subject-based data marts•Conformed dimensions• metadata

• user-facing applications

• business intelligence• decision-support• OLAP• querying• reporting

Decision SupportServers

Metadata

DATA SOURCES DATA ACQUISITION DATA WAREHOUSE DATA DELIVERY DATA CONSUMPTION

Technical Architecture


Building DW Foundation - Technical Architecture Inventory

ERP – Banner from SCT ETL – Power Center from Informatica Data Base – Oracle 9i Models – Star schemas with conformed

dimensions Web Front end tools – Hyperion

Performance Management (Brio), Dash Boards


Building DW Foundation – Data Security, Privacy and Access Policy

Can be defined as striking the “right” balance between data security/privacy and data access

Value of data is increased through widespread access and appropriate use, however, value is severely compromised by misinterpretation, misuse, or abuse

Key oversight principle:Cabinet members, as individuals, are responsible for

overseeing establishment of data management policies, procedures, and accountability for data governed within their portfolio(s), subject to cabinet review and CIO approval

Security& Privacy Access

& Use


Building Subject Oriented Data Marts

Determining Constituency Forming Implementation

Group Conducting interviews Defining Scope and

Timelines Modeling Extracting, Transforming,

and Loading Data Develop Security system Testing

Identify information gaps Identify erroneous data Reinforce common definitions Establish processes to

identify and clean erroneous data

Establish processes to capture missing data

Develop and approve Data Security Policy

Record Meta Data – stored in Informatica repository and accessed with Brio

Alignment between the Technology and Information Quality


Catalyst of Change

Requires marketing and PR Communications Cheerleading Support at the Executive levels Lead by individual respected by all Offering campus training programs “Carrots and sticks” Re-examine existing processes: (month-

end reporting)


Rollout


Recognizing Barriers

People’s resistance to a new tool Expectations on information availability

and usability for decision making are low Habit of relying on Central Administration

to provide information, or on their own sources (many versions of the ‘truth’)

People will need to acquire new job skills Job expectations will need to change


Developing Common Vision

One version of the truth – Warehoused Information was recognized as the only official source of data

Data Experts across campus and across organizational boundaries

Partnering with Human Resources – The DW training was included in Performance Evaluations and Job Descriptions

Training is mandatory at all levels


Communication and Buy-into

Executive briefings: Emphasized changes in analytical culture Recognized Barriers Emphasized that top down approach is needed and ask

for commitment Demonstrated new capabilities via Dash Boards Demonstrated ad-hoc capabilities people within their

organization have Campus orientations

Demonstrated analytical capabilities Introduced training programs and the rollout strategy Communicated Data Policies

Wed site


Data Warehouse Cascaded Rollout Strategy

1. Core Administration

2. Portfolio Level (Cabinet, Deans, Portfolio Managers)

3. Department Level (Directors, Center Directors, Department Chairs, Department Financial Managers)

4. Faculty


Data Mart Release to the Core Administration

Utilizing Data Mart for internal operations More changes to the Data Mart are expected

Establishing data cleanups queries and procedures

Preparing for Campus release: Developing campus training program:

Developing and publishing Dash Boards, and Brio dynamic documents

Developing operational training

Information Quality

Impacting Culture


Initial Tiered Access – Who will have access to what

Dash Board

Analysis performed on the pre-published dynamic

documents

Ad-Hoc capabilities retrieving information from the Data Warehouse

Cabinet; Deans; Department Chairs; Center Directors

Core AdministrationPortfolio/Division level

Department level

Trai

ning

Hig

h

Low


Common Usage

Dash Boards

Simple click away access to the most common topics for analysis

Pre build dynamic queries

Build to address specific needs for information

Ad-Hoc

Meta Topics and published Stars

Ad-Hoc functionality within specific topic


Training Mix

Brio 101 Basic navigation and

mechanics Brio 201

Advanced analytics and reports

Data Training Data mart basics, BQYs,

and star schemas Operational Training

Focuses on practical applications , delivered by business owners

Study Halls Informal, open agenda

Best Practices Demonstration of best

practices, delivered by business owners

One-on-Ones Used to address

specific reporting/analytical needs


Training Program Overview

Track 2

Track 3

Track 1

Brio 101

Brio 101Level 1:

Portfolio/Dept-Specific Pre-Built Docs

Level 1: Data Mart

Basics

Level 2: Advanced

Brio Documents

Dashboard & Portal trainingOne-on-one or small group format

Operational Training

Ongoing Follow-up

High

Medium

Low


Training Philosophy

The goal of the training program goes beyond teaching the mechanics: Need to sell the Brio tool and the project Need to educate on the benefits of the DW Need to emphasize that Banner and the DW

are complementary systems, i.e.,

Need to continue and inspire!We are changing our analytical

culture!


Addressing Information Quality

Establishing processes to capture erroneous and inconsistent data ETL process to identify errors Rejecting data Load data and clearly label errors

Data Audit processes Ensuring that the loaded data reconciles back to

the operational systems

Data


Addressing Information Quality

Establishing Data Stewards roles and responsibilities

The overall data integrity and conformity by instilling business practices and procedures to identify and correct erroneous and inconsistent data recorded in ERP systems

Ensuring that Meta-data is up-to-date Operational Training in information applicability and usage Establishing processes to capture and maintain data necessary

to support decisions Enforcing Common Definitions by facilitating agreement across

organizational boundaries

Data


Establishing services and support

Assessments of information needs Expansion and enhancement of Warehoused

Information Expansion and enhancement of Information

Delivery solutions Process re-engineering Monitoring data quality Support Assessment, Planning, and Analysis Offering full spectrum of campus training

programs


Establishing services and support

Transitioning from Development to Operations Front-End (Hyperion Performance Suite)

Administration ETL (Power Center) Administration Desktop Support and Administration Data Base Administration Dash Board maintenance Brio documents development, support, and

administration Customer Support


Catalyst of Change

Processes and Culture


Changes in our Processes

Some examples on utilization of the warehoused information in our operations:

Assessment and Planning Enrollment Planning Committee meeting utilizes the

enrollment and the admission data in setting the enrollment targets and financial aid goals as they discuss the incoming class (how we did, quality, numbers, diversity, etc)

Retention analysis – analyzing the admissions data to better understand how well the incoming class may be retained next year

Assessment of Employee retention Assessment of Faculty renewal program


Changes in our Processes

Forecasting: Forecast current year sponsor research expenditures. Forecast graduate financial aid commitments Utilize past enrollment, retention, and financial aid information to forecast current and

future year financial aid commitments to determine the affordability of various discount rates

More accurately forecast research awards Utilizing historical research ‘success rates’ in projecting cost sharing commitments

Monitoring and compliance: Daily monitoring of budgets and expenditures from higher levels down to the specifics Monitor and review project to date budgets Monitoring positions budgets vs. actuals and in conjunction with estimated future earnings

are accurately projecting balances Monitoring the allocation of graduate financial aid

Operations Financial information is used in preparing and analyzing the financial statements,

reconciling between the sub-ledger and general ledger, reviewing payroll allocations Credit card reconciliation


Cultural Changes

Empowers decision-makers: Getting accustomed to information availability

Promotes the “no walls” culture: Performing analysis that could never been done before

From ‘MY Data’ to ‘Our Information’ Data Stewards role in improving data quality,

integrity, and conformity Fact based decision making How do we now redirect these costly

personnel hours Enhanced institutional effectiveness


Assessing Data Warehouse

Penetration and Adoption Number of users trained and their role in

organization Number of distinct users connected monthly Number of monthly connection Requests for changes and enhancements Satisfaction surveysValue Shifting IT resources from reporting to other value

added activities Productivity savings on the business side Savings realized by better more informed access to

information


The Dreaded Return on Investment

Calculating ROI Savings in personnel and processing More Effective Financial Aid packaging Effective recruitment strategies Identification of retention issues to

target More fiscal responsiveness


Benefits

Fosters data integrity and conformity One version of the truth Helps to identify erroneous and

inconsistent data Establishing ‘data cleanup’ proceduresValue shifts from data supplier to

analysisTestimonials

http://www.rpi.edu/datawarehouse/dw-testimonials-metrics.html


What’s Next

Cultural shifts: Are we Higher Education and non for profit or Business?

Performance planning processes and assessments

Cultural shifts towards developing Goals, Objectives, measuring outcomes

KPI, Scorecards, Metrics

Administrative Leadership

Academic Leadership

Faculty Operational users

Business Analysts

Pre populated Generic Campus Wide Dash Boards

Pre populated Specific Dash Boards

Research financials Dash Board

Pre build dynamic queries;Meta Topics

Ad-Hoc

As a single source with common definitions, the Data Warehouse is a solid foundation for Scorecards and

KPI

KPI Scorecards Planning and Assessment

KPI, Scorecards Planning and Assessment

Simple Budgeting Planning

Exceptions Alerts Notification

Advance Analytics AssessmentVisualizationMining


Informational Resources

The data warehouse toolkit (Ralph Kimball)

The data warehouse lifecycle toolkit (Ralph Kimball)

Data warehouse design solutions (Christopher Adamson & Michael Venerable)


Informational Resources

Become a member of the data warehouse institute

Visit http://www.datawarehousing.com maintained by DataMirror

Subscribe to listserv from EDUCAUSE http://www.educause.edu/memdir/cg/cg.Html

Visit other schools web sites via http://www.Georgetown.edu/users/allanr/dwconfig/


Questions ???

Ora Fish

[email protected]

?

Data Warehousing: Changing Campus Culture

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