One interesting metric to check the usefulness of Everipedia as a desk reference for data mining is to compare the number of relevant articles. Go to Everipedia (https://everipedia.org/) and search for "data mining". You will get 7 articles.Then go to Wikipedia and search "data mining" You will see 4 articles (overlapped with similar Everipedia articles).
Another example. Try the word "smoothing" which is a popular topic in data analysis. Wikipedia has 4 relevant articles. Everipedia has 9. One may argue that Wikipedia collapses similar content in fewer articles, but this is not true by examining Wikipedia articles. In any event, it is easier to identify the needed topics in Everipedia. Scanning over large Wikipedia articles (assuming that such articles are collapsed into fewer articles) is less convenient.
Such examples can be continued.
Since the number of Everipedia editors is smaller than on Wikipedia, and to get an Everipedia account is somewhat more difficult, this suggests that Wikipedia content was significantly reduced to enforce its notability (which typically means removal of articles). This was discussed in this article on mutilation of Wikipedia.