Visual Analytics

Visual analytics is still a relatively young area of science and research, that makes the visualization of large amounts of data possible, and facilitates its analysis. The term is often used in connection with the term “Big Data”.

Reasons for Visual Analytics

Today, almost everything is recorded statistically. At the same time, the Internet and the open use of Internet media and social networks by the population make it possible to collect vast amounts of data. The amount of data that companies can collect about their customers and external persons is constantly increasing. The larger the amount of data, the more difficult it becomes to process. Conventional IT systems are therefore very often completely overwhelmed. In order to be able to use the data at all, they have to be filtered and cleaned up, as they are of no use to the user because they are stored as raw data.

Founding principles

Visual Analytics is based on the combination of electronic, automated analysis of human data and analytical capabilities. While the computer analyzes the data and can detect certain irregularities as well as regularities, it is the user's responsibility to identify and record trends and developments. Once such trends have been identified, the further analysis process can be controlled. For this process the data is visualized.

Thus, unlike other visualization techniques, Visual Analytics does not serve to clarify already found results, but rather helps to make large amounts of data manageable and evaluable for the human eye. Visual Analytics is a tool for analysis, not for presenting results. This video shows how Visual Analytics works.

Areas of use

Companies in a wide variety of industries can use Visual Analytics for their purposes. The manufacturer SAS, which provides software for Visual Analytics, gives some examples:

  • Retail: better customer segmentation, personalization and localization of customer offerings, prices and assortments to increase sales
  • Banks: recognition of trends and patterns, strategy development, examination of theses, building personal customer relationships thanks to an understanding of customers' needs and preferences
  • Energy: Visualization of plants for the early detection of power failures and defects, prevention of fraud by visualization of the route of power supplies
  • Industry/Production: Early detection of incidents in plants
  • Public sector: Early identification of public sentiment and social, political and economic developments
  • Telecommunications: Early detection of crises, understanding of customer relationship structures, recognition of multipliers
  • Insurance: Delimitation of lucrative customer segments, determination of suitable tariff models

Visual Analytics is also used in various research areas, such as biology, e.g. for the evaluation of human genes, physics and astronomy for the detection of unexpected phenomena, and disaster control for the rapid analysis of natural disasters and other emergencies.

Significance for Online Marketing

For online marketing, the topic of big data is constantly increasing in significance. The more companies know about their customers and target groups, the better they can direct their marketing activities. Interaction on social networks, answering emails, behavior on websites – all of this can be summarized and evaluated today with tracking tools. Also in online marketing, the instrument visual analytics can help to visualize, analyze and evaluate the collected data.

Category