Big Data Requires a Surgical Approach

I've previously posted about the overwhelming volume of data confronting enterprises today, as have countless others.  Although I have hinted at it through many of my blog posts and provided several tangible, hands-on examples in this blog, it occurs to me that I have never overtly stated that "big data requires a surgical approach".  What does this mean?  Essentially, with billions of transactions/records/sessions per day, the volume of data has grown beyond the capability of organizations to handle it.  The enterprise's network data must be sliced up surgically using a variety of different techniques.  Each technique takes a slightly different view/vantage point of the data and produces a reduced, filtered, and more manageable volume of data for investigation.  If this sounds familiar, it is because it is essentially the same approach as I've blogged about previously in posts discussing what I call the "Jumping Off Points" approach.  The approach is simple, straightforward, and effective.  The challenge is finding the most relevant and value-added jumping off points, and continuously working to improve them and to find the next group of relevant and value-added jumping off points.