Jan 23, 2019

Why Is Graph Visualization Important?

From small startups to global brands, every business relies on connected data. Such data is often massive and complex, making it difficult to fully understand and use effectively. Graph visualization makes it simpler to translate densely packed information into a more easily assimilated form that aids analysis and communication. Learn more about graph visualization and how a data analyst uses the technique to find success.

What Is Graph Visualization?

Graph visualization is the process of creating a visual representation of data as a link and node model. This model, called a graph, comprises:

  • Nodes: Individual data points, such as a person's name, telephone number, or e-mail address
  • Edges: A connection between nodes, such as a person having a home address, or investing in a particular company

It's possible to model any data involving connections as a graph. For example, a company database containing the telephone numbers of staff members working in different departments across the company is easy to model as each department links to the name of a staff member, and each staff member links to a telephone number. There are numerous applications available to make modeling a graph easy; just search for graph visualization online to find a range of programs with intuitive interfaces.

What Are the Benefits of Graph Visualization?

At first, graph visualization may not seem particularly important. However, modeling data visually offers several key benefits:

  • Improved comprehension: Representing data as an image of nodes and edges can make it easier to understand. This makes it possible to transmit complex data effectively, and even people who don't have experience with data analysis or technical knowledge of database structure can better understand the information. Graph visualization is particularly useful for meetings and presentations, where it's essential to impart information to decision-makers quickly and coherently.
  • Improved pattern recognition: When data is in a table, it isn't instantly obvious how the content in various cells interconnects. For example, two members of staff who live at the same address would have different entries in the table, with duplicated contact details. When translated into a graph, the edges make it easier to identify patterns and to see that there are multiple people at the same address.
  • Improved problem-solving: Graph visualization programs make it easy to customize your data, and that makes it easier to see how changing elements impacts the system.

Having an Edge in Data Science

An understanding of graph visualization and other analytical techniques has the potential to improve efficiency, making it easier to identify patterns in datasets while aiding communication and comprehension. If you want to know more, browse the Udacity Catalog to discover a range of courses covering fundamental concepts in data science, data analysis, and the real-world application of graph visualization software.