What is Visual Analytics?
Visual analytics is a very powerful approach to detect the expected but more importantly to discover the unexpected. Helps explore raw data so we can understand the data and understand the characteristics ( https://en.wikipedia.org/wiki/Visual_analytics ) .
Many opaque Machine Learning algorithm have no visual analytics, for example Support Vector Machine (SVM). There’s vast application SVM algorithm in all industry globally, We’re First in World to figure out Visual Analytics needs of SVM algorithm after more than one year research on Stroke data.
Geo-temporal Visual Analytics of patients is about their contacts moving in and out of the hospital. This allows Hospital Management filter Geo-location data and querying individual patients; able to see who the patient has been in contact with and knowing their past locations. Visual Analytics provides practical means of exploring analyzing and understanding large and complex raw data sets of patient information. There is a high level of difficulty when trying to understand and analyze data in its raw spreadsheet form. Visualization is essential for analyzing inherently non-visual spreadsheets ( https://www.sciencedirect.com/topics/computer-science/visual-analytics ). Geo-temporal visualization is essential and in its more specialized form such as providing effective and intuitive means for exploring data to detect trends, clusters and recurring events.