Day three of the Edusprint on Analytics kind of returned to day one, taking about the enterprise side of data. A lot of this was repeating what had been said by the representatives from UMBC. The topic on how large amounts of data were managed in HEIs, showed, this time by example of the University of Washington and Arizona State University, how important leadership and top-down governance is for learning analytics.

Institutions react to the challenge of learning analytics as they usually do – by establishing committees! It was therefore no surprise to hear that data governance in UW and ASU was committee driven. They (the committees) in turn spawned a number of task forces, who, I suppose, did the actual job. I am left to guessing how effective this mode of operation really is, but it seems to be the only way universities know. At that the UW approach sounded very heavy handed and formal, presented like the independence of the United States which I do find a little over-exaggerated in approach and self-perception. However, the key aspects of their institutional approach to data are of importance to note:

- consistency in approach to data

- clear models, definitions and processes

Especially clear definitions and consistency of data policies according to defined needs and roles was a point strongly emphasised. Standardisation of data formats and policies (e.g. access rights) make things internally definitely a lot easier. They reduce the need for data cleansing  and guarantee equal access to information across departments and units.

But the presentations also had some omissions. Maybe this is due to these things being of more indirect nature, but no-one talked about the ethical and privacy procedures, if and how they were set up. I consider ethics a fundamental principle of data driven information systems. And the rights of a data subject (an individual student or teacher) to investigate what information about them is made available and how it is used is simply a matter of transparency and fairness. After all, analytics provide support for decision making, including student grading. Therefore, a solid investigation and complaints procedure is as important as creating the information in the first place.