According to the world’s leading analyst and research firm IDC’s Global DataSphere, 65 percent of the global gross domestic product (GDP) will be digitalized, driving over $6.8 trillion in spending from 2022 to 2023.
A higher proportion of GDP will be contributed by digital products and services. Increasingly, companies will face new challenges in the digital-first economy, and they will be required to scale solutions with greater agility.
Knowledge graphs can be used for catching anomalies, discovering patterns, and laying a solid foundation for intelligent solutions such as recommender systems and digital twins. All companies can find relevant use cases.
This InfoBrief covers:
- What knowledge graphs are and how they are used
- Building knowledge graphs
- Fraud detection and risk profiling in banking, insurance, retail, and ecommerce
- Biomarker discovery for life science and pharmaceuticals
- Recommender systems for ecommerce, retail, banking, and professional services
- Knowledge graph-based analytics for ML and AI
- Essential guidance on scaling knowledge graphs for the digital-first economy
- How Neo4j knowledge graphs make sense of complex data for intelligent decision-making
Download your free copy of Knowledge Graphs Power Business Transformation to learn more about the exploding world of connected data.