Visual Analytics

Visual Analytics

Introduction

We are living in the era of technology. There is a lot of advancement. Each day brings new idea and concept. There are also problems with the advancement of technology. We can find a huge amount of data creates problems of storage and privacy issues. The last decade has shown how storage devices has performed and improved. It has been observed that many times data is saved without filtration and reinforcement. Visual Analytics is the latest technology of today (Thomas and Cook 2005).Each industry and firms are producing enormous of the amount of data. Raw data have no importance in certain cases, and we just need to extract information from it. The overloading of information in the data may have certain risks of losing it which includes irrelevant information for the current task to be performed, processed in a different way, and presentation is not correct.

Discussion

The information overloading may create problems of the wastage of time and money. Industrial opportunities are also lost because we are not able to deal with such a huge amount of data. People who are working in different organizations as engineers, doctors, draftsmen, foremen and other workers face to store a huge amount of data and information of their work.

The area of success depends upon the right decisions. Today, there is much advancement and acquisition of comprehensive data is not a problem for many organizations. The problems of dealing immense amount of data have been resolved to some extent. There is still the problem of understanding and analyze the analysis for the future. The technology, which has to resolve such issues, should answer questions regarding the relevant information and an immense amount of data.

The advent of technology of virtual analytics has reduced the problem of information overloading. The aims of virtual analytics are to the data and relevant information transparent to the analytic discourse. The visualization of these problems helps to understand and clear image of these problems instead of leaving this problem with inappropriate results.

Visual analytics improved our processes and models by giving correction and understanding of better evaluation. Visualization has become a part of semi-automated analytics process in which human and machines cooperate with each other using their capabilities in order to produce actual results. The user is the ultimate authority to give the directions of analysis along the desired tasks. This means that visual analytics is providing human and electronic data interaction on a massive scale (Keim et al. 2008). Many people take decisions from the path of data.

Fig. 1. Tight integration of visual and automatic data analysis methods with database,

technology for a scalable interactive decision support.

The preceding sketch shows that the visualization is very important as it is connected with the data and knowledge. The combine effects and knowledge and data will give models and processing. The process, which has shown in the sketch, is interlinked with each other. If any one of the process is missing then, it will become difficult to visualize the data and knowledge and produce ...