The product, US Demographic Knowledge Graph, is in partnership with Woobler.
Woobler is a data connectivity company creating a global footprint of where physical economic activity takes place that connects to risk factors, supply chains, ownership hierarchies and open data sets in the form of a Knowledge Graph.
The first of its kind ‘AI Ready’ Demographic Knowledge Graph connecting 600 million+ demographic attributes that can be easily accessed and exploited via data science, statistical, and data visualization platforms.
- Data Precision`, Data Connectivity and Hierarchical Relationships fully established
- 118,000 Geographic Entities
- 6,000+ attribute types per geographic entity type
- 600 Million+ attribute values
- Simple ways to connect to existing corporate and third-party data sets
For data to be considered in an AI ready state. The following ‘data’ conditions need to be in place:
- Data Connectivity – All the individual data points need to be directly connected or indirectly connected to one another
- Data Precision – Data must be high quality. ‘Dirty’ data will invalidate ML/AI results every time
- Standardized Taxonomies – A consistent approach to classifying and relating data points. ML/AI does not like inconsistent or multiple data schemas
- Hierarchical Relationship Support – Hierarchies play a critical factor in mapping data relationships, data networks, and building decision trees. ML/AI ‘shines’ when
hierarchical relationships are fully supported.
- Data Aggregation/Data Drill Down – Knowledge Graphs support simple methods for data aggregation and data drill drown
- Point in Time (PIT) – All nodes or entities in a Knowledge Graph can support attribute values over time
- Data Visualization Opportunities Increase – Data connectivity greatly expands and enhances data visualization and data reporting
- Data Integration – The ability to provide multiple ways to easily connect to other third party and open data sources
- Single Data Catalog – Simple way to drive data discovery and data access