Big enable Big Data Analytics to help enterprises

Big Data Analytics is a new
fact of business life which requires some tools in place for handling huge
volumes of data sets to identify trends, detect patterns and glean invaluable
?ndings. For realisation of marketing analytics, fraud detection and ?nancial
risk assessment, a mix of business intelligence (BI) tool has been used. This
tool integrates Oracle’s Big Data appliance and Cloudera’s Hadoop distribution
for these purposes. Fast analysis is a signi?cant advantage of Big Data
Analytics so that its tools have a capacity to ?nd the hidden patterns
instantly. Typical tools include Grid Gain for processing large amounts of
real-time data, high-performance computing cluster (HPCC) for real-time
calculations, Storm for dealing with huge data sets with distributed real-time
computation capabilities and Talend for providing many BI service. Harvey investigates
the 50 top tools for Big Data Analytics. These tools are categorised into
platforms and tools, databases/data warehouse, BI, data mining and programming
languages, which enable Big Data Analytics to help enterprises to improve their
processes and performance. With the primary goal to assist companies in making
better business decisions, Big Data Analytics  allow users to analyse huge volumes of data
from different sources such as the database, the Internet, mobile phone records
and locations, as well as sensor-captured information To analyse such huge data
with various formats, the technologies associated with Big Data Analytics cover
a wide range and form a core of open source software frameworks which are able
to support the analysis of large amounts of data sets across clustered systems.
From the literature, it could be observed that PI has been widely implemented
in logistics and supply chain management. PI implementations in manufacturing
?eld are scarcely reported. Additionally, RFID technology is used for
converting various resources into SMOs to build an intelligent manufacturing
shop ?oor. However, studies on how to de?ne SMOs’ behaviours and make full use
of the vast collected data are blank