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I have been watching the dialog about the efficacy of the Course Signals results with interest. I give a tremendous amount of credit to the Course Signals team as I think they have been a positive catalyst for activity in higher ed analytics over the past 7 or so years. I also think it’s healthy to have discussions as to the validity and efficacy of results. If done in a constructive fashion, it will only further the cross-institutional learning that’s happening in our space. The reason I started Blue Canary is that I wasn't seeing enough practical implementations of analytics that produced reasonably sound evidence of positive student outcomes. Hence, this discussion about Course Signals is salient.  Like the e-Literate team, I have also pointed to the Purdue project as…

I caught up with a former colleague the other day.  He's also in the analytics space so we were sharing notes on the state of the industry.  He made a very astute comment about analytics and I like the succinctness of what he said.  We were talking about how there are a number of tech startups focusing on the analysis of the data.  Hadoop and other NoSQL tools that give companies the ability to look at data, transform data, run machine learning processes on data, etc.  That's not the problem, though.  My colleague said, "It's all about getting the data in and moving it out.  It's the ingress and the egress". Keeping the historical trickery of the word 'egress' aside, this is a great statement.  I would argue that if…