Semantic Web Technologies and Machine Learning: A Conjoined Silver Bullet for Big Data

Big data is a concept used to describe data/knowledge characterised by massive size (volume), rapid growth (velocity), and heterogeneity (variety).For efficient and effective decision making in every organisation intrinsically and intricately driven by data/knowledge, it is expedient to guarantee the veracity of this data/knowledge.Unfortunately, the physiognomies of this data impose a grave tailback which has made it impossible for traditional data processing and management techniques to thrive.Critical among these snags are interoperability and integration.Grippingly, semantic web technologies-a collection of standard, methods, and tools for the realisation of semantic web vision-have been touted as a panacea to ameliorating these problems.At the heart of semantic web technologies is machine learning-a computing methodology, and a subdomain of artificial intelligence (AI).This report explicates the intricacies of big data, its benefits, challenges, and as well, the semantic web technologies and machine learning.Furthermore, how these two disruptive technologies interoperate to conjointly address the problems (interoperability, and integration) acting as clog in the wheel to seamless interpretation, processing and management of big data for efficient and effective decision making by machine and human was exposed.At the end of this report, readers are expected to have insight into some critical problems associated with big data, the need to address these problems, and very importantly, how the combination of semantic web technologies and machine learning conjointly help address these problems.