Innovative Approaches to Data Relationship Management in Asset Information Systems

Abstract

Assets are critical working tools in any organisation; their technical nature makes them significant for the effective outcome of strategic designs in today’s fast-growing technological age; hence, proper management of AIS is important for an increase in organisational performance. Such conventional approaches as relational databases or data warehousing are not entirely suitable for dealing with the problem intricacy, size and volatility of today’s connected data. This paper focuses on the assessment of the traditional and novel perspectives of data relationship management in AIS. It also compares traditional approaches like Relational and Object-oriented databases with new/Emerging technologies like Graph databases which optimise data complexity and semantic web technologies for better integration of the data. Also, the integration of advanced computational technologies such as machine learning and artificial intelligence improves predictive analysis and data mining to promote decision-making and organisational performance. Advanced technologies, such as blockchain and cloud applications, advance asset management even more because of their enhanced security, clarity, and expansiveness in approaching relevant databases. Blockchain enhances the features of decentralised record-keeping and immutability, while cloud solutions are scalable storage and computational resources. This paper considers problems like integration, data quality, data scalability and security and also provides some recommendations for further studies to solve these problems. Through examining these developments, the wish for the paper is to contribute to the improvement of asset management as well as decisions in this sphere in the context of growing concern and popularity of technologies.