Introduction
We are connected data engineers 👩🏽🔬👨🏽🔬
- We transform massive unmanageable company datasets
- into meaningful networks (in a graph database),
- and develop queries to surface unique, high-value insights (available as API endpoints).
Our solutions combine connected data and graph databases.
It's All About Relationships
With data connected in networks, you can access information inherent in those relationships. This is how Google's Page Rank algorithm works, by inferring relevance based on the number and quality of connected web pages.
What Is Connected Data?
A data model which treats the relationships between data equally important and is (usually) maintained in a graph database - these are optimised to analyse massive networks quickly at scale.
What Is A Graph Database?
A database architecture designed for connected data. The main technical difference between graph and other types of databases are:
- Index-free adjacency: relationships connecting data entities are created at write time and stored. This allows complex network queries to be performed which are impossible in other databases which typically rely on expensive JOIN operations executed at query time.
- Flexible schema: the schema can be adapted over time, add new entities and relationships without rebuilding the database.
Graph database property model