From bridging data silos to building a data fabric, knowledge graphs provide the foundation for a number of significant use cases across so many industries – from consumer-facing systems like retail to highly regulated like the financial services and life sciences to critical infrastructure like supply chains.
Actioning knowledge graphs can play a key data management role in real-world use cases through data assurance or data insight. To achieve this, an actioning knowledge graph requires integrated, contextualized, quality-assured, and well governed data.
In the book Knowledge Graphs: Data in Context for Responsive Businesses, we help you understand what knowledge graphs are, how to build and use them for actioning and decisioning, and why knowledge graphs are important for data management. The book also details how to use knowledge graph data science for machine learning and AI and for new innovations like digital twins.
Learn how actioning knowledge graphs:
- Provide the foundation for data management functions like data quality, data stewardship, data governance, and data compliance
- Enhance graph-based information search so you search for things and not strings
- Drive contextual decisions like personalization, recommendation, and general next-best action
- Increase in the productivity of data consumers like data analysts and data scientists, bringing high-value insights into operations
In the book Knowledge Graphs: Data in Context for Responsive Businesses, we help data scientists and analysts understand what knowledge graphs are, how to build and use them for actioning and decisioning, and how they power innovations like AI, digital twins, data fabric, and more.
This book is a must-read for data professionals who truly want to understand their data – its lineage, transparency, relationships – and, through the deep context derived from a knowledge graph, build more accurate and unbiased predictions to drive intelligent business decisions.