Years ago I was part of a team of school district employees charged with selecting the new data system we would use for analyzing student achievement results. We made our final selection, which was a system we felt balanced an intuitive interface with the capacity to handle almost any kind of data or analysis (save deeper statistical analysis). We negotiated a contract and had begun developing our implementation timeline when a developer on our team piped up, "It feels a little like we are buying a Cadillac when all we really needs is a Honda Civic." The developer asked if he could have a weekend to work on an alternative to show to teachers. He rolled out a simple, if a little unattractive, solution that teachers seemed to really appreciate. We ended up not signing the contract with the the big data systems provider and saved the district about $350,000.
So, what made the Civic a better system? The locally developed system limited choice. A user only had about six choices with the original version. The designer had curated a collection of views, reports, and drill downs. The designer of the system made choices about what he thought users would find most interesting and be most value-added for teachers (who are incredibly time constrained). The designer treated the data system he designed the way a museum curator sees a collection. The curator does not hang every painting they have. Instead, they chose paintings that represent the period, artist, or mood they are trying to convey for the exhibit. And, when museums develop audio guides they restrict even further what the patrons learn deeply about.
Museum designers must make choices because they are space constrained. Unfortunately, the designers that created data dashboards for educators don't see their users as constrained, so they give them everything. In designing the data systems that we want school leaders and teachers to use we should behave more like museum guides or curators and lead our users to the most likely places for them to find insights.