Data asset management aims to ensure high quality and trusted data.  The purpose of this guidance is to outline the recommended data management functions of a data asset throughout its lifecycle. Those accountable for the data asset should determine if and how each of the data management functions will be supported.

    • Assigns and tracks data management roles and responsibilities (e.g. who is responsible for the storage of the data asset? Who is responsible for approving access to the data asset?)
    • Articulates the principal business objectives, purposes, and uses supported by the data asset
    • Determines the method(s) of data collection (i.e. build on existing data collection tool vs. net new data collection tool) that will meet business, operational and/or analytical requirements
    • Identifies and approves the data types and formats for the key data elements required to support the business objectives, purposes and uses
    • Ensures that Notice(s) of Data Collection and Use are in place and kept current to support the business objectives, purposes and uses
    • Ensures that consent processes are in place, if required
    • Ensures that documentation is in place to allow for effective use and understanding of the data. This may include:
      • A description of the data asset and the supported business objectives
      • A business glossary (functional definitions of key terms)
      • A data dictionary (acceptable data formats)
      • Documentation of the technical data lineage and architecture
      • An inventory of analytics products supported by the data asset
    • Determines which metadata management processes (such as a definition management process) are required and, if so, ensures that they are in place.
    • Approves metadata and definitions as required.
    • Approves the data quality standards for key data elements
    • Determines if a data quality process is required for key data elements and, if so, ensures that one is in place
    • Determines if a quality management process is required to address gaps in data quality and, if so, ensures that one is in place
    • Ensures that appropriate back up plans are in place depending on the criticality, business value, and availability needs of the data asset
    • Classifies the data asset according to the data classification standard at the University
    • Ensures that data protection protocols and technology (collection, storage, access) meet University standards based on the classification of the data asset
    • Ensures that sensitive data fields are appropriately identified
    • Sets data masking standards
    • Understands and communicates the allowable uses for the collected data according to the Notice of Data Collection and Use, University policies and legal obligations
    • Determines the type of role(s) that can access and use these data
    • Determines allowable data linkages
    • Determines the various formats in which data can be consumed
    • Determines if a data literacy training program is required and, if so, ensures that it is in place
    • Sets/approves the conditions of data use including:
      • Appropriate and inappropriate data uses
      • Data literacy training requirements for users
      • Guidance on data downloads
      • How results can be shared
    • Sets/approves the data access approval process based on the confidentiality of the data and breadth of the user base. In accordance with University guidance, elements to consider include:
      • The information and people required to approve access
      • The frequency of data access renewal
      • Methods by which users are properly trained on appropriate data use
      • Processes that ensure that users are adhering to the conditions of data use
    • Sets/approve guidelines on data retention, archiving and destruction, consistent with University guidance
    • Ensures adherence to guidelines on data retention, archiving and destruction