I think there are high quality articles that usually consist of academic articles about computer science/statistics, some announcements of useful open source projects, and interviews/articles by experts renowned in the field.
The frustrating part about DataTau for me is that there are also a huge number of articles that are essentially blog posts, often submitted by the author for self promotion and often consisting of things like "How to be a data scientist" or "Tips every data scientist should know" etc. Some case studies are useful, but many here are to the tune of "I run summary statistics and maybe a basic linear regression on this particular dataset and show pretty graphs".
To me, these articles are, at best, homages to the hype around "big data" and, at worst, are tabloid sounding garbage. They provide little value to anyone but the absolute beginner - and even then, a beginner would likely be better served picking up a book by a well known author in statistics/computer science.
That's not the discredit the value of DataTau - there is some high quality content. Perhaps a solution to the problem could be a tagging feature that allows us to better get access to the content we care about..
