Assessment of
University of Washington
Data Warehouse
Brian Palmer and Laura Reeves
CONNECT, The Knowledge Network
July 15, 2010
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Agenda
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About the Assessment – Scope and Process
Current State of the EDW
Future Vision for the EDW
Moving the EDW Forward
Key Recommendations and Next Steps
Summary
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About the Assessment
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Assessment Scope
The scope of this effort is to provide the University with an Enterprise
Data Warehouse (EDW) Assessment Report to address the following:
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Validate the strategy and provide additional recommendations on all aspects
of data architecture and information delivery.
Assess current technologies in use and provide recommendations for
improvement.
Evaluate the overall program approach including organization and support
models, staffing levels, operations and project delivery processes.
Assess program risks to the existing strategy, architecture and technologies.
Assess progress made since the last review of the BI program.
Evaluate proprietary data access control system.
Evaluate the iStrategy feasibility study.
The scope of this assessment did not include:
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Scoping and costing of specific projects (OPB, RADC, etc.)
Identification of new opportunities or quantification of associated business
value.
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Assessment Process
To achieve these goals, CONNECT has gathered insight for this report
by:
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Interviewing key stakeholders, users and team members of the current
data warehouse to determine the business value they are receiving from
today’s EDW, and to ascertain an understanding of their future Business
Intelligence needs.
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Evaluating current state data solutions including; technical
environments, data architecture, and processes in use for the delivery of
Business Intelligence
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Reviewing documentation to understand the history, tactical plans,
projects and long term strategy for Information Management placed in the
context of the broader business and technical strategies of the university.
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Interviewing Business Intelligence leaders from Peer Institutions to
provide additional context to the assessment and associated
recommendations.
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The Current State of the
EDW
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Progress and Notable Accomplishments
• Staffing
– Have assembled a group of quality individuals able to provide a strong
foundation for the team needed to move the EDW forward.
• EDW Environment
– Providing a stable and reliable environment where source system data
can be accessed for operational reporting.
– Deploying databases which are segregated, maintained, and being
upgraded to SQL Server 2008 using new features such as partitioning.
– Consolidated reporting technology onto the Microsoft product line.
– Providing role-based security in accordance with federal and state data
access control and privacy stipulations.
– EDW data extracts feeding other data stores supporting additional
reporting and analysis.
– Progressing on plans for evolving the data architecture of the EDW.
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Progress and Notable Accomplishments
• Reporting
– Highly disciplined process to create standard reports
– Currently over 1,700 users accessing more than 150 standard reports
– Created two financial analytical cubes with critical subsets of data to
support flexible access and analysis.
• Business Metadata
– Metadata concepts are clearly understood as evidenced by the initial
work and accountabilities of the Data Management Committee.
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Support
– DSS web site to communicate critical details about the EDW with links
to DMC web pages with data definitions and security roles.
• The site is one of the best that we have seen implemented.
– Actively engaged with user issues through the Reporting Services SIG.
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EDW Business Value to Date
Consumers of EDW sourced data provided many positive insights on the value
proposition of the existing EDW in terms of the data’s ability to support
improved quality and efficiency of reporting for their business areas. Here are
several examples that highlight this point:
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Paper report replacement resulting in improved operational efficiency,
making data available for use sooner, and reducing mainframe reporting
overhead. Significant impact identified in the financial management decision
support area.
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Data mart / cube created to support financial analysis to review what
has been identified as taxable (use/sales tax). This resulted in the
identification of the potential refund of millions of dollars, per Purchasing
and Accounting.
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Overcoming operational systems shortcomings through structured
reporting. Creating reports using a disciplined processes to ensure report
quality, and providing them to users in a well documented reports library.
Academic Advisement for Mathematics and Computer Science are
examples of areas that have benefited from the EDW structured reporting.
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Business Perception
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While significant progress has been made, the current data warehouse
capabilities are not able to meet user expectations.
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The biggest challenges we heard from the business users of the EDW
stated as simply as possible were:
– We are unable to view information across the organization (i.e. lack of
integrated data).
– It is too hard to use.
– It takes too long to get things done.
– The source application systems are out-dated.
– De-centralized organization and culture make it difficult to know who
has what data, and how to get it.
– Use of the data warehouse has been for financial and operational
reporting rather than analysis.
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While some changes are needed from an IT perspective, it is also important
for the institution as a whole to:
– Begin to shift towards using the DW to drive institutional effectiveness
– Take a more analytical approach to decision making
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Current Business Intelligence Challenge
• Highly de-centralized organization and culture creates challenges.
• Fragmented data environment with many “stove pipe” data marts.
• Lack of integrated data and limited Business Intelligence tool
capabilities make it time consuming and technically challenging to
get information out.
• Gaps exist in foundational components of organization and process.
• Limited data definitions and inconsistent hierarchies impact ability to
view across the organization.
• EDW requires the addition of other data sources to provide a more
complete view of the organization.
• Fragmented support to users coming from 5 separate decision
support teams outside of the EDW.
• Campus systems limitation have resulted in a focus on data
warehousing as an operational reporting environment, as opposed to
focusing on analyzing institutional effectiveness.
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Current EDW Data Architecture
Source
Systems
Staging
Layer
Extract Raw
Data
HR-Payroll
Systems
Subset &
Summarize
HR Data
User
Access
Transform &
Warehouse
Minimal
Transformations
HR Data
ODS
(Current
Data)
Structured Reports
Finance
FR Data
Mart
Financial
Systems
Financial
Data
Financial
Data
Structured Reports
GL Data
Mart
Student
Admin Sys
Academic
Data
Academic
Data
Census
Day Mart
Academics
Master
Data
HR Data
Mart
Structured Reports
UWSDB
(Student )
Current Structures
Departmental and External Data Stores
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The Future Vision for the
EDW
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Future Vision of Business Intelligence
Criteria for the future EDW data architecture to provide a credible,
consistent and reliable data environment:
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Integrates data from different source systems as well as departmental data.
Supports different types of historical data including transaction detail, static
snapshots (such as census day), etc.
Continues to support the ability for operational inquiry and reporting.
Provides mechanism to integrate departmental data w/core institutional data.
Continues to provide appropriate security in the environment.
Data organized to facilitate ease of use and good query performance.
Is cost effective to use and to enhance (extensible).
Supports timely development of new reports.
Provides users with other flexible methods to access information with an
emphasis on “self-service” and ad-hoc analytics.
Employs data quality management practices.
Provides transparency through business Metadata content and presentation.
Has high performing incremental load of source data.
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EDW Data Architecture Vision
Source
Systems
HR-Payroll
Systems
Staging
Layer
Extract
Raw
Data
HR-Payroll
Data
Financial
Systems
Financial
Data
Student
Admin Sys
Student
Data
Facilities
Serv. Sys
Research
Admin Sys
Integration
Layer
Integrate
&
Cleanse
Integrated
Presentation Layer
User Access
Business
Intelligence
Applications
Transform
for User
Access
HR Data
Financial Data
Academic Data
Other Data
HR, Financial,
Academic,
Facilities,
Advancement,
Other…
Analytics
Integrated
Departmental Data
Departmental
Data
Dashboards
Facilities
Data
Departmental
Data Entry
Research
Adm Data
Scorecards
Analytics
Advancement Sys
Advancement Data
Other
Systems
Other Sys
Data
Current Structures
New Structures
Archive
Dept Input
Structured Reports
ODS
(Current
Data)
Structured Reports
Departmental and
External Data Stores
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Business Value: Investing in the Future Vision
Many opportunities exist to provide added value to the university:
Gaining Greater Control Over Information Assets
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The Institution has an obligation to the community and the individuals it serves to
protect the information accumulated in the performance of its mission. The EDW
can play a significant role in demonstrating the Institution’s commitment to using
due diligence in its effort to maintain control of information assets.
Improving Business Process through Data Integration & Analytics
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Good decision making depends on the availability and use of common,
consistent information. Investing in a well designed integrated data environment
in the EDW accompanied by strong business metadata could significantly
enhance the role of the EDW in moving the organization towards proactive
decision making.
Managing Costs
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Through the Return on Investment associated with EDW related business
process improvement initiatives.
Through the elimination of costs associated with the current highly decentralized
and redundant information environment.
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Moving The EDW Forward
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Short-Term Approach to Business Intelligence
• Incorporate recommendations into the current priority project work as
first step towards the future vision architecture.
• Leave much of the existing environment in place to continue to
support any existing users and reports.
• Focus on building out the data structures needed to provide flexible
integrated institutional data:
– Leverage the data as it is being sourced into the warehouse today,
however, develop a new integration layer.
– Build and Deploy a new integrated presentation layer based on
dimensional data structures using conformed dimensions with
appropriate history.
– Purchase and deploy a “classical” Business Intelligence user interface to
enable end-user self-service reporting and ad-hoc analytics (examples
include MS ProClarity and Business Objects).
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Short Term EDW Data Architecture
User Access
Source
Systems
Staging
Layer
Integration
Layer
Extract
Raw
Data
HR-Payroll
Systems
Business
Intelligence
Applications
Integrated
Presentation Layer
Transform
for User
Access
Integrate
HR Data
Transform &
Warehouse
HR Data
Financial Data
Academic Data
Fin,
Academic
& Select
HR Data
Analytics
Dashboards
HR Data
Financial
Systems
Financial
Data
Subset
&
Summarize
Student
Admin Sys
Student
Data
Select
HR Data
Financial
Data
Scorecards
Academic
Data
Structured Reports
Academic
Data
Production Data Extracts
Archive
UWSDB
(Student )
ODS
Current EDW Structures
(Current
Data)
HR Data
Mart
Finance
New EDW Structures
Structured Reports
Departmental and
External Data Stores
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People and Process
Gaining true value from a data warehouse is more than moving data
more efficiently. It is highly dependent upon the people and processes
to support the entire environment.
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Staffing Recommendations
– Add specific roles to manage warehouse specific work including
metadata management, testing, data modeling, and end-user support.
– Fill these roles with people that have data warehouse experience.
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Work Intake and Prioritization Recommendations
– Recognize different types of work: Project, Report Development,
Management of Access and Security, and Maintenance
– Track the volume of requests and effort associated with involved with
each type of work.
– Develop a business prioritization process to set direction, manage
priorities, measure the outcomes.
– Allocate resources based upon priorities.
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People and Process
• End-User Support / Client Facing Services
– End-user support must be recognized as key factor for wide-spread
adoption of the data warehouse.
– Support resources can report through business or IT.
– Develop tiered support approach to meet the full range of departmental
needs.
– Address the need to integrate user support services across the five
decision support teams outside of the EDW.
– Training services should be expanded to include new BI tool
functionality, data content, and metadata usage.
• Several recommendations have also been made to begin
addressing data quality and make refinements to the system
development lifecycle.
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Key Recommendations & Next Steps
Our recommendations are targeted towards helping UW address these challenges
in a realistic way given the current economic environment. The following high
level recommendations summarize the assessment report details:
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Business Partnership
– Business Leadership is necessary for the EDW program to succeed. Clarify
business accountabilities and make the commitments.
– Establish practices that ensure priorities, expectations and commitments are
clearly communicated throughout the organization.
– Business constituents must be advocates for the EDW.
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Initial Project and Staffing
– Allocate resources at the level required to effectively complete data warehouse
development projects:
• Immediately acquire incremental resources to ensure successful completion of
the OPB/ABB project. (Estimated as an additional 4.5 FTE’s)
• Fill the critical roles that are currently absent from the EDW team.
• Incorporate business expertise (Business Analysts) into project teams.
• Concurrent projects would require additional incremental staff & increase risks.
– External resources should mentor UW staff to reduce long term dependence.
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Key Recommendations & Next Steps (2)
• Data Architecture
– Make it a priority to document and publish institutional data definitions,
often called business metadata.
– Leverage the data as it is being sourced into the warehouse today.
– Develop a new integration layer to prepare the data for the presentation
layer.
– Extend the EDW data architecture to support self-service reporting and
analysis . Specifically build a presentation layer with dimensional data
structures that use conformed dimensions and appropriately handles
history.
– Re-engineer the beginning layers of the EDW data architecture in
conjunction with the replacement of the source application systems.
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Key Recommendations & Next Steps (3)
• Data Delivery
– Purchase and deploy a “classical” Business Intelligence user interface
for the enablement of end-user self-service reporting and ad-hoc
analytics.
– Build and deploy a suite of starter business intelligence applications.
These should provide flexible, parameter driven reports that can be
easily modified on the fly to support analysis and decision making.
• Deployment and Support
– Sufficient resources must be allocated to focus on support and
deployment of business intelligence (Client facing services ) provided in
combination from business and IT.
– Determine tiered support model and method for delivering coordinated
support services.
– Employ a work intake and prioritization mechanism.
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Peer Institution Benchmarking
• Conducted phone interviews and a survey with the following Peer
Institutions:
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University of Michigan
Rensselear Polytechnic Institute (RPI)
University of Illinois
Seattle University
Princeton University
• University of Michigan Highlights
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Most comparable peer in terms of size and research
DW started in 1994
Replaced core systems starting in 1998 (PeopleSoft)
Provide reporting and analysis to a large audience
• Business Objects has 5,500 users
• M-Reports has 7,000 users
– Internally developed report delivery interface for “guided analysis”
– Large EDW Staff with 28.8 FTEs
– Metadata Presentation Capabilities (delivered with each project)
– Next generation DW expansion is on the books and in planning phase.
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iStrategy Evaluation
• iStrategy reviewed the UW environment to assess the feasibility,
benefits and challenges of implementing their products (June, 2010)
• CONNECT reviewed iStrategy assessment, but did not directly
participate.
– In general we agree with UW observations based on iStrategy’s
extremely candid evaluation.
– iStrategy provides strong user interface to facilitate reporting & analysis
– iStrategy provides a library of higher education metrics which are likely
to require extensive customization.
– The iStrategy product line does not support an integrated data model
– Core benefit of the iStrategy product line is their integration with third
party applications. Since UW is not using these packages, this would
not be a benefit.
– Need to explore technical direction of their product line – currently using
SQL Server 2005 and MS ProClarity
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University of Michigan - iStrategy Experience
University of Michigan implemented several iStrategy products. The
critical lessons learned from their experience include:
– Biggest benefit was to launch the DW team and expand their skill set
into dimensional data structures.
– Implemented using the University of Michigan developed interface. End
users did not know they were using iStrategy.
– Would suggest implementation without customizing to get your feet on
the ground. Then customize as appropriate.
– Are planning to move away from the iStrategy product with the
implementation of their new integrated data warehouse architecture.
– The vendor provided excellent guidance and consulting during the initial
financial implementation project.
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Summary / Conclusions
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EDW Assessment Summary
The University of Washington has been investing in the data
warehouse environment for a number of years. While there has been
progress, there are still many needs that are not being met with the
current Enterprise Data Warehouse (EDW).
• The current EDW does provide value to the institution.
• There is a common and realistic understanding across the university
of what the current EDW can do, as well as its limitations.
• There is also an appreciation for the commitment, quality and work
of the current EDW staff.
• The DSS Team understands and acknowledges the challenges with
the current EDW and has developed plans to address these issues.
• The assessment validates that the plans are fundamentally sound
and with the additional refinements suggested should move forward.
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EDW Assessment Summary
The University of Washington is poised to make significant strides in
how the data warehouse is used across the institution. Critical factors
to achieve this success include:
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Business Commitment
– Make the financial investment to implement the plans.
– Gain executive support to ensure organizational alignment around a
clearly defined set of priorities and goals.
– Determine organizational roles with responsibility, accountability and
resources to carry out the work.
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IT Commitment
– Execute the plans effectively
– Facilitate the process to define roles and work associated
– Provide the technical and data environment to empower the University.
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Partnership – is crucial to achieving good results.
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Assessment of University of Washington Data Warehouse