Getting Your Data Graph-Ready After deciding on the technology and the key operational and logistical questions you want to answer with graph, your next step is to build a graph data model.

Graph databases open up views of interconnected data to help users discover and analyze relationships between datapoints, be it in customer transactions or internal operations. Knowledge graphs ...

The use of data and analytics at Colgate-Palmolive is grounded on the principle that investments in data and analytics must deliver measurable business value.

In recent years, knowledge graphs have become an important tool for organizing and accessing large volumes of enterprise data in diverse industries — from healthcare to industrial, to banking ...

The acquisition comes as the visual communications company reached over 75 million monthly active users, up over 30 million in the past 12 months.

The four pillars of graph adoption This confluence of graph analytics, graph databases, graph data science, machine learning, and knowledge graphs is what makes graph a foundational technology.

DTSA 5511 Introduction to Deep Learning Same as CSCA 5642 Specialization: Machine Learning Instructor: Geena Kim, Assistant Teaching Professor Prior knowledge needed: Calculus, Linear algebra, Python ...

Until the nineteenth century, Friendly and Wainer tell us, most modern forms of data graphics—pie charts, line graphs, and bar charts—tended to have a one-dimensional view of their data.