Graph data closes the gap between the way humans and computers view the world. While computers
rely on static rows and columns of data people navigate and reason about life through
relationships. This practical guide demonstrates how graph data brings these two approaches
together. By working with concepts from graph theory database schema distributed systems and
data analysis you'll arrive at a unique intersection known as graph thinking. Authors Denise
Koessler Gosnell and Matthias Broecheler show data engineers data scientists and data
analysts how to solve complex problems with graph databases. You'll explore templates for
building with graph technology along with examples that demonstrate how teams think about
graph data within an application. Build an example application architecture with relational and
graph technologies Use graph technology to build a Customer 360 application the most popular
graph data pattern today Dive into hierarchical data and troubleshoot a new paradigm that comes
from working with graph data Find paths in graph data and learn why your trust in different
paths motivates and informs your preferences Use collaborative filtering to design a
Netflix-inspired recommendation system
