Decentralized Intelligence and Big Data Analytics Reciprocal Relationship

Since the awareness of the availability of Big Data hit the business world in the early 2000s, more and more organizations have switched to data-driven approaches to everything from hiring to product development. Gartner has reported that up to 60 percent of big data projects won't make it into implementation. That means that understanding the need for analytics isn't enough; you need to be able to collect data and put it effectively to work. Furthermore, artificial intelligence (AI) along with its subsets of machine learning and deep learning as powerful methodology and technology for big data projects is plagued by data bias and data quality conundrums. At the same time, there has been discussion over how blockchain could help in tackling these abandoned data projects as well as data reliability concerns, and it turned out that bringing blockchain technologies to big data analytics and creating so-called decentralized intelligence offers serious benefits by providing businesses with greater visibility, security, and efficiency in managing their big data, but also rendering some research questions that we aim to address in this study such as: can agents train a model without needing to disclose their data?, can the third parties contribute to an AI model in an influential way?, at the same time, we expect a reciprocal relationship between decentralized intelligence and Big data analytics which pose questions such as: how effectively decentralized intelligence impacts big data analytics? and how effectively big data analytics impacts decentralized intelligence?