Post by account_disabled on Feb 21, 2024 23:05:46 GMT -6
Big data has been accessible for some time now. We can store them, work with them, analyze them... It seems that the limits are blurring and now the challenge is to find a way to display the information in the most useful way possible. A form of data visualization capable of adapting perfectly to user needs. Do you know what intelligent data visualization is ? data visualization Photo credits: istock Sparky2000 Data visualization: the importance of a good tool Data visualization tools , to be useful to the business: They have to facilitate the task of diving into the information to extract all the intelligence contained in the mass of data. Preferably, they should incorporate the science of human visual perception into their data visualization techniques.
Its information exposition capabilities must never go against the understanding of the data or its contextualization. These tools should increase the clarity of the presentation while decreasing the amount of time needed to Chinese Student Phone Number List make sense of the data being presented. The ideal is software that allows people to find things they don't know, but should; such as extreme values, hidden trends, and rapidly changing data sets. That's precisely where data visualization provides real value. The return on investment comes from how quickly you can find something that you couldn't see before, increasing your ability to act on it immediately. What's new in data visualization The developments in this area point in a very clear direction. Today, a new generation of visual data discovery technologies are emerging that incorporate psycho-visual principles specific to the human species. Its main features are: They produce easily understandable visualizations.
They are able to display data for visualization even before storing it. They encourage proactive interaction with information. The discovery that is carried out through intelligent data visualization provides the user with a motivating experience and a source of improvement. This way of working encourages the user to be able to perform tasks such as: Reorganize data on the fly. Set priorities quickly. Change hierarchies when necessary. Filter irrelevant information. Isolate the relevant discoveries they find. These analysis-oriented interactive visualizations should be easy to understand in a very short time, since their main benefit is the reduction in the time frames required for consistent and accurate decision making. To achieve this, the providers of this type of software services rely on the study of visual attributes such as color, size, shape or relative proximity, among other elements that appear on the screen; which are fundamental to human understanding of a data visualization. Thus, the design of one of these data visualization systems has to allow the information to be easily intelligible, and its navigation intuitive, even when dealing with complex data or data sets subject to constant change.