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InfoAccess Service

About the UW-Madison Data Warehouse

The University Data Warehouse is a subject oriented, point-in-time, inquiry only collection of University data.  The Warehouse data is extracted or derived from the production databases of the University's information systems. 

The data is presented in a format familiar to the campus user and to allow for ad hoc access without compromising the performance and integrity of operational systems.   This information gives authorized individuals more timely access to data needed to solve problems that extend beyond the daily operational requirements of the office.  

The Data Warehouse contains detail and summary data and historical data depending on the associated business needs.

Characteristics of the UW-Madison Data Warehouse

Content

  • Subset of operational data
  • May include summarized or derived data without supporting detail
  • Current and/or historical
  • Not the official source of information

Freshness

  • Point-in-time
  • Refreshed on a set schedule which may vary for each view. 
  • Expect the published schedule to be met 95% of the time. 
  • When the schedule cannot be met a resolution can be expected within 48 hours.
  • The refresh schedules are set based on factors including campus business needs, cost, and data custodian recommendation.

Availability

  • Data Warehouse is available from 8am-5pm Monday through Friday.
  • The system may be available 'after hours' but is not supported for access during this time.
  • Accessing information 'after hours' may result in incorrect results if a table is being loaded while the query is being run.

Volatility

  • Constantly changing and evolving
  • Customers may be required to change any previously saved queries
  • Customers are notified via email distribution list when modifications are make to existing views.

Suitability

Customers are responsible for evaluating whether the data warehouse and InfoAccess service is suitable for their particular use. This means accepting the terms of the content, freshness, availability, and volatility of the data warehouse.