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v 1.1 published 3/13/2017  Archived 3/23/2020

Strategy Statement: Data & Analytics provides leadership and support to UW academic and administrative units in delivering institutional data for decision making.

Vision: Satisfied and Empowered Customers; Reliable, Integrated, Well-Defined Data for the University.



Increasing demand at all levels of UW for timely, accurate and consistent information for decision making and operational efficiency.

Current: Develop education, training, and outreach to put users in control of data assets; implement Knowledge Navigator (KN) to increase understanding of data assets.

Planned: API Management; data lineage; canonical data model

Future: Data mashup tools; self-service BI

Easy-to-find, easy-to-access, easy-to-understand data enable more effective, and serendipitous use of data assets.

Users have access to more enterprise data sets they need to make better decisions.

Demand for short turnaround times.

Demand for fast performance, modern user experience, and increased self-service.

Current: Improve capacity planning; develop clear processes for "adopt or not"; implement high speed search; automate testing & deployment

Planned: Support new Data Governance model; implement API Management; master data management;

Future: Self-service BI

Test & deployment automation, along with reuse of common technology patterns, practices, and services, speed solution delivery.

Re-established data governance removes roadblocks to availability of data assets.

Increasing and changing threats to data security, and changes to the compliance landscape. 

Current: Increase data security plans

Planned: Create culture of data security; new Data Governance model; canonical and master data;

Future: Develop next-generation data access tools

Data privacy and security are built into solutions.

Growing number and diversity of enterprise data sources.

University buy-over-build approach requires new approaches to data acquisition and integration.

Current: Enterprise Integration Platform (EIP); adapt to source changes (on-going); event notification

Planned: Reassess DAC/SMAT;

Future: Data mashup tools; orchestration of business processes;

Management of data assets keeps pace with the growth of data sources.

Growth in technology to support predictive analytics.

Ability and willingness of customers to "roll their own"

Current: Extend and operationalize data science capabilities;

Planned: API Management; OAuth;

Future: Implement data mashups;

Best-of-breed vendor solutions and emerging technology increasingly replace existing local solutions and amplify use of data assets.

Re-allocation of resources to large ERP efforts impacts delivery of data and analytics capability.

Future: Analyze options for new funding models.

Funding model for data and analytics matches demand.

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