基于TDWI成熟度模型的制造企业大数据采用成熟度度量

F. Retrialisca, U. Chotijah
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引用次数: 3

摘要

背景:大数据技术已经在印尼的多个领域得到应用。大技术的采用为研究提供了巨大的潜力,特别是在制造企业实施大数据方面取得了成果。数据仓库协会(TDWI)成熟度模型是一种工具,可以使用5个主要维度来衡量大数据的“现状”实施状态。成熟度水平表示当前组织对大数据技术的调整能力水平。目的:本研究旨在衡量制造企业PT. XYZ实施大数据技术的成熟度。这种度量被认为是非常重要的,因为它可以了解管理结构化数据和大量数据的过程,并提供更透明的报告。这可以帮助公司做出决策,提供良好的信息,因此公司可以增加利益相关者的信任。方法:采用TWDI成熟度模型工具对研究数据进行定性分析。采用访谈技术检索受访者数据,通过关注TDWI中的5个维度和50个指标,制定访谈准备指南。结果:研究表明,大数据技术在公司整体上的实施已经达到了企业采用的水平。基础设施、数据管理和分析维度已经达到了企业采用级别,而组织和治理维度仍处于早期采用级别。结论:利用TDWI成熟度模型工具、访谈指南等定性方法,综合考虑TDWI中存在的5个维度和50个指标,衡量制造企业采用大数据技术的成熟度水平。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Maturity Measurement of Big Data Adoption in Manufacturing Companies Using the TDWI Maturity Model
Background: Big data technology has been used in several sectors in Indonesia. Adoption of big technology provides great potential for research, especially achievement in the implementation of big data in manufacturing companies. The Data Warehousing Institute (TDWI) Maturity Model is a tool that can be used to measure the state of "As-is" implementation of big data using 5 main dimensions. Maturity level shows the level of organizational ability to adjust big data technology currently.Objective: This study aims to measure the level of maturity in the implementation of big data technology in manufacturing companies PT. XYZ. This measurement is considered very important because it can know the process of managing data that is structured and has a high volume of data and provides more transparent reporting. This can help the company in making decisions that provide good information, so the company can increase the trust of stakeholders.Methods: This study uses qualitative methods to analyze research data using TWDI Maturity Model tools. Interview technique is used to retrieve respondent data where interview preparation guidelines are made by paying attention to 5 dimensions and 50 indicators in TDWI.Results: The research showed that the implementation of big data technology in the company as a whole has reached the level of corporate adoption. Infrastructure, data management, and analytics dimensions have reached the corporate adoption level while the organizational and governance dimensions are still at an early adoption level.Conclusion: To measure the maturity level of adoption of big data technology in manufacturing companies can use qualitative methods with TDWI Maturity model tools, interview guides for data retrieval by considering the 5 dimensions and 50 indicators that exist in TDWI. 
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