Architecture Components - Big Data Analytics: Disruptive Technologies for Changing the Game - page 37

Figure 4.3: “Slice and dice” using product categories
more than one entity. A sub-class shares the attributes of its super-class. There-
fore, both scooters and electric scooters should have two wheels. While the
classic product catalogs were static and were managed by administrators without
organized feedback, the unstructured analytics provides the ability to make a
dynamic hierarchy, which can be adjusted based on usage and search criteria.
A more general representation of conceptual entities is found in ontology,
which is an abstract view of the world for some purpose. 21 Ontology deines
the terms used to describe and represent an area of knowledge. Ontologies are
used by people, databases, and applications that need to share domain informa-
tion (a domain is a speciic subject area or area of knowledge, like medicine,
tool manufacturing, real estate, automobile repair, inancial management, and so
on) and may include classiications, relationships, and properties. 22 With formal
ontology, we can create a “Semantic Web,” which can provide structural extracts
to machines, thereby providing them with ability to extract, analyze, and manipu-
late the data.
Qualitative Comparisons
Once we start to categorize and count unstructured text, we can begin to extract
information that can be used for qualitative analytics. Qualitative analytics can
work with the available data and perform operations based on the characteristics
of the data.