Nokia Data Marketplace
Secure data exchange with blockchain and AI/ML orchestration
What is data marketplace?
The value of a data marketplace is to facilitate the data trading and exchange process as efficiently and securely as possible while removing obstacles that prevent buyers and sellers from performing their activities.
Nokia Data Marketplace is a proven, secure and scalable solution for business to business (B2B) data exchange and monetization. Based on a unique set of features and secured by blockchain, the Nokia Data Marketplace provides enterprises access to rich datasets as well as AI/ML orchestration capabilities.
The solution supports multiple data sharing and trust models to cater to the requirements of different datasets and customer needs. With our flexible as-a-service business model, customers also benefit from rapid time to market and optimized total cost of ownership.
Nokia blockchain marketplace
Nokia Data Marketplace uses private permissioned blockchain to enable trusted contracts and secure transaction mechanisms
Multiple data sharing and trust archetypes
The underlying data marketplace infrastructure offers a range of data science processing archetypes for the member organization to select from
Data format agnostic
Data format are not standardized to provide flexibility for data providers and data consumers to perform data transformation as per specific needs or algorithms
Features and benefits of Nokia Data Marketplace
Secure data exchange
Easily trace data exchange among units within a large enterprise or an ecosystem
Digital Catalogue, trusted contracts, transactional mechanisms
Innovative & simple to use analytics
Easily execute algorithms on data stored in multiple locations without actual data transfer, using federated learning
Data privacy and security
Data is not stored in the marketplace, the solution just controls the secure data exchange between buyer and seller
Use cases for federated learning and data monetization
Increase equipment availability by optimizing maintenance planning, spare parts stock levels and employee resources
Predictive traffic management
Improve urban traffic management strategies to avoid congestion and pollution
Supply chain automation
Optimize logistics network performance, reduce delays by automating settlements between the stakeholders
Improve intelligence exchange between government agencies for faster actions
AI-based health recommendations
Enable clinical decision support systems to tailor treatment to individuals or patient groups
Environmental data monetization
Increase yield, minimize herbicides and optimize the use of fertilizers depending on actual (non-uniform) soil conditions by algorithm-driven control of farm equipment