One of the important aspects of enterprise data that we learned in the earlier section
is the data consolidation and sharing that requires unconstrained collection and ac-
cess to more data. Every time change is encountered in business, it is captured and
recorded as data. This data is usually in a raw form and unless processed cannot be
of any value to the business. Innovative analysis tools and software are now available
that helps convert this data into valuable information. Many cheap storage options are
now available and enterprises are encouraged to store more data and for a long time.
In this section, we will define the core aspects of Big Data, the paradigm shift and at-
tempt to define Big Data.
to in terms of volumes. Traditional database engines cannot scale to handle
these volumes. The following figure lists the orders of magnitude that repres-
ents data volumes:
• Data formats generated and consumed may not be structured (for example,
relational data that can be normalized). This data is generated by large/small
scientific instruments, social networking sites, and so on. This can be stream-
ing data that is heterogeneous in nature and can be noisy (for example,