Amalgamation of Enterprise System with Big Data

Running head: BUSINESS INFORMATION SYSTEM
Business Information Systems
Name of the Student
Name of the University
Author’s Note:

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BUSINESS INFORMATION SYSTEM
Table of Contents
Introduction................................................................................................................................2
Discussion..................................................................................................................................2
Enterprise System...................................................................................................................2
Big Data.................................................................................................................................3
Conjunction of Enterprise System with Big Data..................................................................4
Conclusion..................................................................................................................................8
References..................................................................................................................................9

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Introduction
Enterprise system or ES is the larger scale application software package, which is
solely responsible for supporting the business processes, data analysis in the complex
companies or reporting and information flows (Sykes, Venkatesh & Johnson, 2014). When
the enterprise system works with PEAS or packaged enterprise application software systems,
the custom developed system helps in supporting the needs of the organization. There are
several types of enterprise systems. They are ERP or enterprise resource planning system,
customer relationship management software and enterprise planning system. The systems of
business intelligence and data warehousing are the typical enterprise wide packaged
application software as they never directly support the execution of various business
processes (Sykes, 2015). There are various advantages and disadvantages of enterprise
system within any typical organization. Enterprise system is extremely effective when it
works with big data.
The following report outlines a brief discussion on the amalgamation of enterprise
system with big data. The rapid growth in big data helps to highlight the requirement of the
newer tools, techniques and methodologies for augmenting the better practices. Several
tangible benefits are obtained after the correlation of existing data in wider range of sources.
This report will be highlighting the several significant factors that prove that enterprise
system works better when it is added with big data.
Discussion
Enterprise System
Enterprise system is software application, which has several cross organizational
capabilities in any particular organization (Pollock & Hyysalo, 2014). This type of enterprise

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system is responsible for allowing all kinds of communication and collaboration throughout
the organization. Enterprise systems are eventually built on the software platforms, like
Fusion of Oracle or NetWeaver of SAP as well as databases. From the perspective of
hardware, the enterprise systems are storage, associated software and server, which the larger
businesses utilize as foundations of information technology infrastructure (Walther et al.,
2013). All of these systems are designed for the purpose of managing larger volumes of
critical and vital data. Hence, these enterprise systems are so designed so that they could
easily provide high level of transaction performances or security and privacy of data.
Although the systems of business intelligence or data warehousing are enterprise wide
packaged application software. These are sold by the enterprise system vendors, as they are
not directly supporting the execution of the business processes (Soja & Paliwoda-Pękosz,
2013). The most popular and used types of enterprise systems are ERP or enterprise resource
planning software, CRM software or customer relationship management software and
enterprise planning systems.
Big Data
Big data can be defined as the larger data sets, which the traditional data processing
application software is inadequate in dealing with. The major challenges of big data mainly
include data storage, transfer, capturing of data, updating, sharing, information privacy and
visualization (Swan, 2013). The most significant concepts of big data are volume, variety and
velocity. These three concepts are together termed as 3Vs of big data. This big data even refer
to the proper utilization of predictive analytics or user behaviour analytics. The other
advanced methods of data analytics help in extracting value from the data and thus is limited
to the specific size of the data set. The significant analysis of data sets is responsible for
finding newer correlations to the spotting of business trends and thus helping in other forms