Your data: secure and standardized.
The precondition for collecting all this data and making it usable for instructors, technologists, and learning specialists is ensuring that the information is standardized, categorized, and tagged. Considering that each application may have its own conventions for naming each data field, the task of data aggregation has remained largely prohibitive in higher education.
As Brad Wheeler, Vice President for IT and Chief Information Officer at Indiana University, writes about data laundry, (which is “the legitimate process of transforming and repurposing abundant data into timely, insightful, and relevant information for another context”) the effort required is only surpassed by its value. Doing it once in a university-controlled consortium such as Unizin is safer and more efficient than any alternative available to universities today. To further assure security, the consortium model allows for a shared governance around various pieces of the analytics and the uses of the data by our Members.
Our data laundry includes standardizing “dirty clothes.” The Unizin Common Data Model (UCDM) provides a common language and model for data that comes from a variety of tools and systems. This uniformity* is essential for researchers, faculty, application developers, and other staff studying the data landscape.
* The data aligns with and extends the Common Education Data Standards (CEDS) and with event standards such as Caliper and xAPI.
Unizin Data Platform
Once data has been cleaned and organized, it can be managed and manipulated. Since no vendor had yet developed an adequate architecture for data management, Unizin developed a comprehensive solution - the Unizin Data Platform (UDP).
The UDP offers data products and services for learning analytics, application development, research, and business intelligence at the institutional level. The UDP collects and standardizes data from a variety of sources using the UCDM and gives researchers and analysts access to data marts, real-time event processing, and APIs. Member institutions save time and effort and the process of data management is simplified.