The experience I acquired from these projects provided me with an invaluable knowledge about student data systems. Like many super-users on campus, this knowledge has been both useful and valuable to me now as a university resource.
Is it good to have knowledge limited to a handful of people?
I would argue that it’s time to let go of our “super-user pride” and become more open about data knowledge. Institutions need to think of ways to democratize the knowledge and accelerate the learning curve for anyone who needs access to data.
There are four ways to do this:
1) Allow users direct access to the data. This does not mean access to production, or violating FERPA or HR privacy; instead, open secure query databases for direct access with a variety of tools. This requires careful monitoring, but the rewards can be enormous.
2) Give users the necessary documentation. Access to data dictionaries with functional and technical definitions is a great start. Create forums for asking questions and mentoring.
3) Allow users to answer their own questions with data. There is no better way to learn than to have your own question to work on. Training is often theoretical or unrelated to actual jobs (take a SQL class and see what I mean). Real projects create real learning.
4) Get users to share the knowledge as it is learned. Collaboration through data dictionaries, shared documentation, and user groups will ensure the investment in learning does not create a new class of super-user gatekeepers.
Data quality: Build trust among all users
Several things affect data quality. Some “bad” data come from the old “garbage in, garbage out” principle. At the same time, there are also “good” data with “bad” communication, so clean data with no communication can still create “garbage out.”
Many schools are producing vast amounts of high-quality data for their campus. However, owing to a lack of trust in the data, much of this information is not being used. When people are not included in conversations about the data definitions, or they just see data as numbers coming out of a black box, it can lead to doubt.
It’s important to create transparency and shared documentation in data management. Without both transparency and open collaboration during the process, it is very difficult to create trust. No report is ever easy enough or pretty enough to overcome a lack of trust.
Improving data management is the key to success
When institutions struggle with institutional reporting, they assume that the existing technology is not good enough, so they look for a new tool. I have seen schools move through the landscape of reporting and BI tools only to find that they continue to have the same problems. There are some great tools out there, and you can do some amazing things with new technologies.
However, before throwing more money at the problem with a new tool, you should investigate how your campus is communicating about data.
With a small investment in data management best practices, campuses can create a “value multiplier” for existing investments in reporting technologies. The institutions that are seeing a return on their technology investments have started with the fundamental understanding that, in order to turn data into information, everyone must be involved in the conversation.
Brian Parish has been working in education technology since 1995, with a primary focus in enterprise data systems. Parish is the president of IData Inc., a higher-education technology consulting and software solutions firm. IData provides services in IR, IT, and system implementation; its product line includes DataCookbook.com, an online collaboration tool designed to serve as a central repository for data management and governance.