Big Data is such a catchall phrase.  Besides the on-going arguments about the definition of Big Data we'd like to inject a different debate.  Namely, what is and also what should be the balance between the data side of Big Data and analytics side of Big Data.  

So here is a crude measure to figure out what is the current balance between data and analytics.  The search index trend over the last 18 months or so between the search terms "Big Data" and "Big Data Analytics"  That picture is shown here, where the blue line is the trend line on "Big Data" and the red line is the trend line on "Big Data Analytics".


Two things pop out.  One is Big Data started before anything thought was given to the analytics side of the equation.  Second, the analytics side of Big Data is not gathering as much speed as Big Data broadly.  

This is troubling.  Why?  Because in the end Big Data should not be about the acquisition, manipulation and storage of just more data.  You have to know why you need to collect it, what you intend to do with, and what question the data should help answer.  And that has everything to do with the kind of analytics you are going to subject the data too.  

The real work of Big Data comes before you ever start collecting one kilobyte of data.  More on that next time.