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Technology

Graph visualization: why it matters

September 28, 2017

Graph visualization is the visual representation of data - nodes and edges - stored as a graph. It's an important tool for businesses sifting through large amounts of complex data. We'll look at some of the major benefits of graph visualization and its different use cases.

What is graph visualization

The first step to understanding graph visualization is understanding what a graph is. Also called network, a graph is a collection of nodes (or vertices) and edges - also called links or relationships. Each node represents a single data point such as a person, a phone number, or a transaction. Each edge represents how two nodes are connected: a person possess a phone number for example. Graph analytics provides algorithms that help data scientists and data-driven analysts answer questions or make predictions. This way of representing data is well suited for scenarios involving connections, like social networks, telecommunication networks, protein interactions, and a lot more.

Graph visualization is when the nodes and edges of a graph are displayed in a visual way. Dedicated algorithms, called layouts, calculate the node positions and display the data on two (sometimes three) dimensional spaces. Graph visualization tools like Linkurious Enterprise provide user-friendly web interfaces to interact and explore graph data.

Graph visualization
A simple graph visualization made with Linkurious Enterprise – 9 nodes representing investors (blue), companies (green) and market (orange) and 8 edges indicating how they are connected.

These visualizations are data modeled as graphs. Any type of data asset that contains information about connections can be modeled and visualized as a graph, even data initially stored in a tabular way. For instance, the data from our example above could be extracted from a simple spreadsheet as depicted below.

The data could also be stored in a relational database or in a graph database, a system optimized for the storage and analysis of complex and connected data.

In the end, graph visualization is a way to better understand and manipulate connected data. And it offers several advantages. 

Why is graph visualization important?

Interactive visualization tools are an essential layer to identify insights and generate value from connected data. There are a number of reasons why graph visualization is useful:

  1. You will spend less time assimilating information because the human brain processes visual information much faster than written information. Visually displaying data ensures a faster comprehension which, in the end, reduces the time it takes to make decisions and take action.
  2. You have a higher chance of discovering insights when interacting with data. Graph visualization tools offer the possibility to manipulate the data. It encourages data appropriation and  increases the possibility of discovering actionable insights. A study showed that managers who use visual data discovery tools are 28% more likely to find information in less time, than those who rely solely on managed reporting and dashboards.
  3. You can achieve a better understanding of a problem by visualizing patterns and context. Graph visualization tools are perfect for visualizing relationships but also for understanding the context of the data. You get a complete overview of how everything is connected which allows you to identify trends, relationships, and correlations in your data.
  4. It’s an effective form of communication. Visual representations offer a more intuitive way to understand the data and are an impactful medium to share your findings with decision-makers.
  5. Everybody can work with graph visualization, not only technical users. More users can access the insights since specific programming skills are not required to interact with graph visualizations. This increases the value creation potential.

Let’s illustrate some of these benefits with a very simple example. We have a data sample of eleven individuals with information about who works with who. Below is the same data sample in two formats: a table and a graph visualization.

Data table
Table of our data sample
Graph visualization example
Graph visualization of our data sample

In our second format, we’ve modeled the relationships between persons as edges to obtain a graph.
While in the first table it’s pretty hard to understand how the people in the data set work together, we get a clearer view with the graph visualization. We are able to distinguish two groups and an individual who seems to be the link between them, a pattern that we did not notice at first in the table.

Graph visualization applications

Many industries are using graph technology to leverage their connected data and reach their goals. At Linkurious, we work with companies from a large variety of fields. Their common point, however, is the need to find connections or understand dependencies within their data. Below are a few examples of typical use cases of graph visualization and the organizations who use it.

Anti-financial crime

Banks, insurance companies, and financial institutions have a common urgency to face: fraud. From money laundering to insurance fraud to bank fraud, each of these organizations is required to detect fraud schemes that may be highly complex. The data often combine customer information, claims details, financial records, and watch-listed individuals or organizations. For them, graph visualization is a good way to detect suspicious connections or patterns. It’s also an intuitive way to investigate fraud rings and criminals networks.

Cybersecurity

Today you’ll find cyber, or IT, security in many large organizations, financial institutions, and security consultancy services. Organizations need to protect themselves from vulnerabilities like zero-day vulnerabilities and DDoS or phishing attacks. They collect data from servers, routers or application logs and network status in order to detect suspicious activity. Graph visualization is a great tool to digest this data and detect suspicious patterns at a glance. It makes the finding of compromised elements easier and more time efficient thanks to the visual exploration of connections.

Intelligence

Almost every government has its intelligence agency. To support law enforcement, national security or military objectives, these organizations collect and analyze data from various sources. The detection and identification of terrorist networks, for instance, became a crucial objective in the past decades. Visualizing connections between people, emails, transactions or phone records is a key to ease such investigations. 

IT operations management

The field of IT operations management keeps growing with our increasing reliance on computer systems, networks and the growth of the Internet of Things. But because of the growing complexity of infrastructures, managing networks is often a challenge. Graph visualization allows IT managers to visualize dependencies between their assets (servers, switches, routers, applications, etc). It’s an intuitive way to perform impact or root cause analysis.

Enterprise architecture

Numerous mature organizations implement enterprise architecture management. It consists of synchronizing business and IT data. The goal is to analyze, plan, and transform the business processes, applications, data, and infrastructure to maintain the organization ability to change and innovate. With graph visualization, enterprise architects can visualize the organization assets and their dependencies. It helps to conduct impact analysis, obtain insights on the current situation (as-is) and plan the right actions.

Life science

Protein interactions, drug compositions, disease networks: for life science data analysis, almost everything is about connections and dependencies. However, the large amount of data often makes it difficult for researchers to identify insights and look for dependencies. Graph visualization makes large amounts of data more accessible and easier to read. It has many different applications, from linking drugs with adverse events and diseases with phenotypes to visualizing a network or understand how diseases spread.

How to visualize graph data with Linkurious Enterprise

Linkurious helps organization extract insights from complex connected data. Linkurious Enterprise offers an easy-to-use graph visualization and analytics platform, accessible to technical and non-technical users.

Used by teams of analysts and investigators, Linkurious Enterprise provides an intuitive UI to visually explore and investigate complex data from multiple sources. It facilitates the discovery of new insights and speeds up decision making.

Learn more and start leveraging the value of your connected data.

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