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Date - September 14, 2016

Contributors: Aaron Powell, Anja Canfield-Budde, Paul Schurr, Paul Prestin, Bart Pietrzak, Rob McDade, John Mobley, Cassy Beekman

Strategy on a Page for Enterprise Information, Integrations, & Analytics


Strategy Statement:

EIIA provides leadership and support to UW academic and administrative units in delivering institutional data for decision making; is responsible for data integration, metadata management, information design and architecture; manages the enterprise integration platform, the enterprise data warehouse, enterprise web services, business intelligence systems, tools and data management solutions; provides training. Good data good; bad data bad.


  • Satisfied & Empowered Customers
  • Reliable, Integrated, Well-Defined Data for the University

1. Change Drivers

What are the big changes in the environment (technology, business, financial, risk, etc..) that you need to respond to?  See the Toolkit for Generic Change Drivers and help.

  • Increasing need at all levels of UW for timely, accurate information for decision making
  • Campus need for more efficient administration of their units' business
  • Emerging trends in the field:
    • pressure to create the next-generation B.I. solutions
    • Pace of technology change and need to keep expertise up to date
    • Addition of predictive / data science on top of existing operational data needs.
    • Ability and willingness of customers to "roll their own"
  • Increasing and changing threats to data security
  • Shift in funding:
    • staff from the decentralized services to large ERP efforts
    • increasing number of FTEs on non-perm funding
  • University buy over build approach presents new challenges and requires new approaches to data acquisition and integration.
  • Growing number and diversity of enterprise data sources
  • Customer (and University) demand short term around times.
    • Necessity to govern and understand this increasingly valuable resource
  • Customer demand easy to use, cross domain, domain agnostic views of University data.
  • Customers demand:
    • fast performance
    • modern user experience
    • accurate and consistent data
  • Regulatory changes

3. Initiatives

What projects, business cases or initiatives do you have underway or you should do to respond to these change drives and deliver the outcomes and future state.


  • Capacity planning
  • Develop education, training, and outreach
  • Build out capability for technological orchestration of business processes (phase 1)
  • Enterprise Integration Platform (EIP)
  • Develop clear processes for "adopt or not"
  • Architect solutions for change
  • Managing existing solutions and incremental improvement
  • Deployments - Increase automation (EDW)
  • Adapting to source changes (on-going) 
  • Work with CISO on Data Security Plans
  • Knowledge navigator (KN) 
  • Metadata management
  • Event notifications
  • High speed search
  • Data science capabilities (Extend and Operationalize)


  • Develop proposal for new Data Governance Model
  • Create culture of data security
  • API Management
  • Data lineage tool (aka Ray's Proposal)
  • Canonical data model
  • Master data management
  • O-auth
  • Data governance support
  • Reassess DAC/SMAT (not just technical)


  • Create data mashups (local & enterprise data)
  • Develop next-generation data access provisioning tools
  • Build out capability for technological orchaestration of business processes (phase 2)
  • Build tools to evaluate and communicate the impact of the shift in funding from one service to another
  • Self-service BI


2. Outcomes/Future State

What does responding to the change drivers do to how we do business or work in future?  What are the business outcomes (how we will do things differently and the value to the business) or new ways of doing work in the future?

  • More robust data management by University leaders
  • Consistent, transparent access to data
  • Solutions leverage emerging technology trends
  • Positive user experience working with easy-to-find, easy-to-access, easy-to-understand data:
    • Enabling serendipitous use of data assets.
    • Enable customer self-service
  • Business priorities drive funding and staff allocation
  • Ensure we have, and can manage, the data to meet campus needs


  • Deliver faster
  • Data privacy and security are built into solutions
  • solutions use common patterns, practices, offerings (i.e. web login)

Add your compelling story(ies).

Think about the story you can tell looking at the drivers and future state/outcomes and tell one or more compelling stories to motivate your team and others into action.  See the Toolkit for help.  You can also attach a PDF or link to another page or site with your story.