Skip to main content


Showing posts from October, 2021

Working with Graphs in Oracle Analytics - Node Ranking

Node Rank Graphs describe relationships between various entities in a dataset. When defining graphs, then nodes correspond to entities and edges represent relationships between them. Node Ranking measures the importance of nodes in a graph.  For example, in social networks we have people. We represent people, members of a social network, as nodes. The relationships, e.g. friendship, are represented as links between two people. People with a lot of friends are often called influencers, as their decisions, opinions, etc. are exposed to more people than other members of the network. Their rank is higher. Marketing departments tend to focus on and work with these influencers in order to get the maximum reach within their networks. Measure that measures this phenomena is called Node Rank .  We can find similar use cases practically everywhere. In transportation, for instance, the network of airports has more and less important airports. Airport hubs are those airports which have the most c

Working with Graph in Oracle Analytics - Intro

You can find the following definition about Graphs and Graph theory on Wiki :  In mathematics, graph theory is the study of graphs, which are mathematical structures used to model pairwise relations between objects. A graph in this context is made up of vertices (also called nodes or points) which are connected by edges (also called links or lines). A distinction is made between undirected graphs, where edges link two vertices symmetrically, and directed graphs, where edges link two vertices asymmetrically. Graphs are one of the principal objects of study in discrete mathematics. In essence, graphs are used to model various types of relationships. In case of business analytics, graphs can used in sales and marketing departments to perform recommendations of the products to particular group of customers that are somehow related to some other group of customers, in manufacturing they can be exploited to manage inventory more effectively due to better planning of materials and semi-produc