of that data is fairly obvious or fairly easy to ascertain. In addition, there typically are not
much contextual data to begin with when it comes to repetitive unstructured data.
Therefore, the emphasis is almost entirely on the need to manage volumes of data.
But with nonrepetitive unstructured data, there is a great need to derive the context of
the data. Before the data can be used analytically, the data need to be contextualized.
And with nonrepetitive unstructured data, deriving the context of the data is a very
complex thing to do. For sure, there is a need to manage volumes of data when it comes
to nonrepetitive unstructured data. But the primary need is the need to contextualize the
data in the first place.
For these reasons, there is a “great divide” when it comes to managing and dealing with
the different forms of unstructured data.
Chapter 1.3: The “Great Divide”