Guide to Data Quality

Data quality is a major challenge for most institutions as they begin to develop a data-enabled approach, but it is a critical early step. Any answers generated by your data will only be as accurate as the data itself. This resources highlights some of the key steps to ensuring the quality of the data you have access to.

Assessing the Success of Analytics-led Interventions

Analytics is an evidence-based methodology that prizes empirical information. As such it is appropriate that institutions should be able to provide an evidential foundation for the success of analytics itself. HEIs should seek to iteratively assess the effectiveness of their analytics strategy to ensure that it is having a positive impact on students’ experience. This document briefly discusses some of the considerations and challenges that should be born in mind when institutions are attempting analytical self-reflection.

Topics for Consideration when Selecting an LA Vendor

Although bespoke platforms are not essential for developing a data-informed approach, for any institution that is considering doing so, identifying the right platform is important. This document lists a number of essential considerations for opting for a reporting system that is right for your institution’s reporting needs.