531 Paper1

Topics: Business intelligence, Data mining, Data management Pages: 17 (3009 words) Published: April 14, 2015


CPSC 531 Assignment-1
Big Data Application in Retail
By Usha Paniram Brahma CWID: 802173195

California State University, Fullerton
Computer Science Department
Professor: Dr. Chun-I Philip Chen
February 17, 2015

Table of Content
Abstract4
1. Introduction5
2. Literature Review6
2.1 Definitions6
2.1.1 Big Data Analytics6
2.1.2 IT Technology and Frameworks in Consideration8
2.1.2.1 Map Reduce8
2.1.2.2 Hadoop9
3. Apache Hadoop for Retail10
4. Critique and Limitations of Technology11
5. Current Stage of Big Data in Retail11
6. Future direction for Big Data in Retail12
7. Discussion13
8. Conclusion and Implications14
REFERENCES16

List of Figures
Fig 1: Map Reduce………………………………………………………….5 Fig 2: Architecture of Hadoop System ……………………………………..8

Abstract

To enhance the competition, ambition and efficiency, the realm of retail, like many other industries have accrued a range of software applications over time from the warehouse to the point of sale. Big Data can launch merchandising and operational effectiveness that reduce costs; lead to a plan of action to understand customers even before they realize what they want and provide information to considerably revise marketing, sales and customer relationships. However, deploying Big Data applications and infrastructure to underpin them can result in a high level of intricacy. These tasks have depended upon an array of tools to manage scalability, handle deployment and management. But a paradigm shift in the architecture, deployment, design and management of Big Data applications is advancing, implementing an easier and faster result for retail industry in procuring the benefits of Big Data. In this paper I will summarize briefly about obtaining methods to assemble various information from making use of Big Data frameworks, evaluate the strengths and challenges of deploying and maintaining robust Hadoop clusters for Retail and enhancing Big Data application in Retail to adopt new technology quickly and wisely.

1. Introduction

The retail industry reacts rapidly to changing and developing trends that may impact customer demand for pricing and offers, explicit products, customer service, and other features of customers understanding of a retail brand. Earlier, retailers analyzed business data and any other customer report data that was accessible. Today, a huge amount of data is available to them from various retail web-sites, mobile location data from computers, smart phones and tablets, in-store video and analytic systems, customer demographics, embedded sensors and social media to name a few. This chunk and collection of data available to retailers provides abundance of new opportunities to raise revenue, control costs and converse vying threats. Big Data applications distinguished by the presence of abundance and complex data sets, signifies the acknowledgement of new visions and designs to better understand customer behavior. But in a marketplace infested with delayed economic growth and large costs, retailers are struggling aggressively to boost their share of customers’ wallets. The ascent of a new breed of digital customers that wants personalized and...

References: http://www.ibmbigdatahub.com/interactive/big-data-retail-industry
Rabi Prasad Padhy (2013) Big data with Hadoop and Map Reduce http://www.iaesjournal.com/online/index.php/IJ-CLOSER/article/view/1508/pdf
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