Big Data and Its Characteristics Big Data is huge amount and variety of data needs to be
stored, processed, distributed and analyzed to enhance decision
making and processed optimization. Big Data is generated and
collected from myriad data sources like: Search Engine Data, So-
cial Media Data and Stock Exchange Data.
The concept of Big Data is based on 3V which they: vol-
ume means huge amount of data, velocity means high speed of
data in and out, and variety means different data types and sourc-
es [1]. Also, other papers add, veracity indicates to the uncertainty
of the data, variability is not similar the same as variety. if the
meaning is constantly changing it can have a huge impact on data
homogenization. and value, it is the most important thing, big
data should contain valuable data to support businesses [2].
The big data can be divided into three parts: Un-
structured Data type (like Word, Text, PDF and video, audio),
Structured Data type (like relational data and Databases) and
Semi-Structured Data type (like XML file).
Data Mining Data mining (DM) can be defined as the process of ex-
ploring valuable and hidden knowledge and laws from unknown
data; this is from a technical view point. From business perspec-
tive, data mining is the extraction, processing and analysis of
large amounts of data, producing some values access to critical
information and knowledge that can support making business
decisions [18]. Data mining is also known as Knowledge Discov-
ery in Data (KDD). Data mining can be defined as the process of
discovering patterns from huge data and making predictions to
obtain new data [13].
The KDD process has five steps as shown in Figure 1
Figure 1: The KDD process [19].
