Data Lake: Promoting a Mega-Tool for the Assessment Lifecycle
- Author(s): Shafer, Sharon
- Peterman, Dana
- Mizrachi, Diane
- Grappone, Todd
- et al.
Published Web Locationhttp://qqml.org/wp-content/uploads/2017/09/Shafer-QQML-2019-20190527_Data-Lake.pdf
A recently created Library Strategic Plan at the University of California Los Angeles (UCLA) identified the need to integrate a culture of assessment throughout the organization in order to encourage more data informed decision-making processes. Our Assessment for Change Team (ACT) was formed and charged with spearheading this cultural evolution. This case study will discuss the development of a home-grown tool that assists with assessment brainstorming, and acts as a central repository for assessment products – the Data Lake.
The UCLA Library consistently ranks among the top academic libraries in the United States serving 45,000 students in125 majors. It employs approximately 100 librarians and 350 full-time staff working in more than a dozen library locations all over campus. Library units report to the University Librarian through her four Associate University Librarians and management staff.
Data Lake is an enterprise wide collaboration platform used for managing change and an assessment culture within the Library. First, a guided questionnaire assists with brainstorming and planning of assessment ideas while invoking dynamic reports and notification of resource managers at critical points within the assessment lifecycle. Next, the platform enables abstracting, indexing and storage of raw data and assessment tools while supporting dynamic visualizations, reports and dashboards. Finally, connections with service tickets and project plans are promoted as assessment plans morph into reports and data informed decisions to launch or change projects.
We see our greatest challenge as managing and maintaining one solution as an organization's assessment systems and data holdings expand. As much data is sensitive and subject to privacy issues and access restrictions, it is necessary to ensure a data management policy is in place and being followed. Management and governance of data assets requires oversight and maintenance of permissions and data retention policies as well as addressing the technical debt of maintaining connections and policies with external systems such as BOX for use as a true large data repository.