March 8, 2012, Stephen Wolfram wrote in the Wolfram|Alpha Blog: The Personal Analytics of My Life mapping data about his e-mail usage, time spent in meetings and even keyboard usage.
August 30, 2012 he introduced W|A Personal Analytics for Facebook introducing a first round of capabilities to let anyone do personal analytics with Facebook data.
In the September 2012 issue of the Harvard Business review Magazine I read the article with the above title. It motivated self-measurement, auto-analytics ... with Stephen's efforts of "self-awareness" and insight.
And then the author, H. J. Wilson challenges with the core question of all analytics efforts: do we use massive data to find patterns and features or models that describe the input/output relations. Which patterns will lead us to "improvements". Do we apply unsupervised or supervised (machine) learning - in technical terms.
To ask the question, whether it is enough to create patterns is adequate; the answer is: it is usually not.
But I think, many experts in various fields still underestimate the objectives and achievements of the Wolfram|Alpha team: to collect massive data and implement every known model, method and algorithm to compute whatever can be computed about anything. This may include methods that create models from data and apply them to describe the dependencies of behavior and better working performance - the objective of auto-analytics.