## 7 Big Data and Blockchain in Decision-Making
### Facilitating Predictive Analytics and Automation
#### 7.2.1 Predictive Analytics in Decentralized Systems  
Predictive analytics uses extensive information to detect patterns, trends, and correlations that might offer valuable insights into forthcoming occurrences. Data quality and dependability are of utmost importance in decentralized systems. Blockchain technology guarantees the security, accuracy, and immutability of the data utilized for predictive analytics. Every piece of data entered into a blockchain is unchangeable and marked with a timestamp, resulting in a reliable historical record that predictive models may depend on [110].  
In a decentralized supply chain network, blockchain has the capability to document and track each transaction and movement of commodities. Subsequently, big data analytics may utilize this past data to forecast variations in demand, anticipated interruptions in the supply chain, and the most advantageous levels of inventory. Predictive models utilize historical data trends to provide projections, enabling stakeholders to make well-informed decisions regarding production schedules, shipping routes, and inventory management. This ultimately improves the efficiency and resilience of the supply chain [111].  
Lastly, the application of predictive analytics in the financial industry allows for the forecasting of market movements, the evaluation of credit risks, and the identification of fraudulent actions. The transactional data that is utilized in these studies is guaranteed to be inaccurate and unchangeable, thanks to blockchain technology. Identifying investment possibilities, managing risks, and improving compliance with regulatory requirements are all things that may be accomplished with the use of predictive models by financial institutions. It is possible to make proactive decisions thanks to this predictive power, which in turn helps to reduce the likelihood of prospective losses and improve financial performance.  
Enhancing Decision-Making with Predictive Analytics and Automation Improvements in decentralized decision-making are made possible by the integration of predictive analytics and automation through smart contracts. These improvements include the provision of timely, data-based insights and the autonomous execution of choices. This collaboration not only ensures that decisions are made based on the most accurate and up-to-date information, but it also makes the process of putting these decisions into action more effective [112].  
It is possible, for example, to use predictive analytics in a decentralized logistics network in order to estimate delivery timeframes and identify any delays that may occur. Because smart contracts have the potential to autonomously reroute shipments, adjust delivery schedules, and communicate with necessary parties, they ensure that logistical activities are carried out in a manner that is both efficient and effective. The deployment of this automated decision-making capability in real-time leads to a reduction in operational dangers and an improvement in overall performance. All of these benefits are achieved simultaneously.  
Challenges and Potential Issues in Integrating Big Data and Blockchain for Decentralized Decision-Making  
In order to successfully capitalize on the benefits of integrating big data with blockchain technology for decentralized decision-making, it is necessary to solve several obstacles and potential concerns. These obstacles encompass technological, operational, and regulatory aspects, and it is vital to tackle them in order to achieve effective implementation and long-term viability of these technologies.