SOFTWARE POSITIONING TOOL TO SUPPORT SMES IN ADOPTION OF BIG DATA ANALYTICS USING A CASE STUDY APPLICATION

Matthew Willetts, A. Atkins
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Abstract

Big Data Analytics is widely adopted by large companies but to a lesser extent by small to medium-sized enterprises (SMEs). SMEs comprise 99% of all businesses in the UK (6 million), employ 61% of the country’s workforce and generate over half of the turnover of the UK’s private sector (£2.1 trillion). SMEs represent 99% of all businesses in Europe and 90% worldwide. Therefore, assisting them to gain competitive advantage by the adoption of technology, such as Big Data Analytics is an important business initiative. The aim of this paper is to outline the process in which a positioning tool based on theoretical frameworks has been developed to help SMEs analyse their readiness to adopt Big Data Analytics using a case study. Previous work has identified 21 barriers to adoption and a methodology based on theoretical frameworks was developed to produce a positioning tool Holistic Big Data Analytics Framework for UK SMEs (HBDAF-UKSMEs). The paper outlines a case study based on a software development company to utilise this HBDAF-UKSMEs framework to assess the readiness using the proposed scoring tool for the adoption of Big Data Analytics based on three stages: pre-data analytics, business intelligence and Big Data Analytics.
软件定位工具,通过案例研究应用程序支持中小企业采用大数据分析
大数据分析被大公司广泛采用,但中小企业(sme)的应用程度较低。中小企业占英国所有企业的99%(600万),雇佣了全国61%的劳动力,创造了英国私营部门一半以上的营业额(2.1万亿英镑)。中小企业占欧洲所有企业的99%,占全球企业的90%。因此,通过采用大数据分析等技术来帮助他们获得竞争优势是一项重要的业务举措。本文的目的是概述基于理论框架的定位工具的开发过程,通过案例研究帮助中小企业分析其采用大数据分析的准备情况。先前的工作已经确定了21个采用障碍,并开发了一种基于理论框架的方法,以产生定位工具英国中小企业整体大数据分析框架(HBDAF-UKSMEs)。本文概述了一个基于软件开发公司的案例研究,利用这个HBDAF-UKSMEs框架来评估采用大数据分析的准备情况,使用拟议的评分工具,基于三个阶段:数据前分析、商业智能和大数据分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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