Analysis and Research on Enterprise Science and Technology Innovation Strategy Based on Big Data

Guoqiang Chen, Bifang Huang, Xiaoyu Wei, Bowen Chen, Haojie Liao

Research output: Contribution to journalArticlepeer-review


This study explores the analysis of enterprise technology innovation strategies based on big data. In the context of the digital economy era, big data has become a key driving force for enterprise technological innovation. By collecting, integrating, and analyzing big data, enterprises can gain insight into market trends, optimize product development, improve operational efficiency, and achieve intelligent strategic decision-making. This article first outlines the core characteristics of big data technology and its application status in enterprise technological innovation. Furthermore, an in-depth analysis was conducted on how big data can assist enterprises in achieving technological innovation, including product innovation, service innovation, and business model innovation. At the same time, the challenges faced by enterprises in utilizing big data for technological innovation were also discussed, such as data privacy protection, data security, and technological updates. Finally, this article proposes strategic recommendations for enterprise technological innovation based on big data, including strengthening data governance, optimizing data-driven decision-making mechanisms, enhancing data analysis and mining capabilities, and building an open innovation ecosystem. By implementing these strategies, enterprises can better utilize big data resources, promote technological innovation, and achieve sustainable development.

Original languageEnglish
Pages (from-to)394-405
Number of pages12
JournalRISTI - Revista Iberica de Sistemas e Tecnologias de Informacao
Issue numberE67
Publication statusPublished - 2024


  • Big Data
  • Decision Tree Model
  • Prediction


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