Visual displays of data

            This means presentation of data in a graphical or a pictorial format and is seen by most disciplines as a contemporary correspondent of visual communication. The main goal of data visualization is to pass information efficiently ad clearly through graphs, information graphics and plots. Arithmetical data may be set using lines, tools and bars in order to communicate a quantitative message visually. If this is doe effectively, it helps the user to analyze and reason about the data and evidence. It also helps in making complex data simpler, usable, accessible ad understandable. It helps the users who have particular analytical tasks like comparing and understand causality in following the task. Tables are normally used where users for users to look up a certain measurement. Various types of charts assist in showing relationships or patterns in the data for one or various variables (Tufte, 2006).

            Data visualization is a science and an art because some see it as a branch of graphic analysis while other people view it as a grounded theory. It is used by decision makers to view analytics that are visually presented in order to grab complex concepts as well as identifying new patterns. Interactive visualization helps in taking concepts further through using technology to present into graphs and charts. This process has been used for centuries from maps and graphs to the innovation of pie charts. It has been made it possible by computers to process huge quantities of data in a faster manner. It has recently become a fast developing merge of art and science. It is meant to make changes to the corporate landscape in the next few years to come (Pauwels, 2006).

            Big data is significant as it is a potential for great opportunity in big Companies and banks. Due to the manner that human brain processes information, use of graphs and charts to picture large amounts of difficult data is simpler than using reports or spreadsheets. It is a rapid and easy way to express ideas in a universal manner. It also makes it possible to conduct tests with different situations through adjusting slightly. It is also used in recognizing areas that require concentration or development. They also help in clarifying the factors that influence the behavior of customers. They also help in understanding the kind of products to be placed in a particular place. Data visualization is also used in predicting sales volume. However, there are challenges that are involved in data visualization such as IT team being faced by many requests for information. Decision makers are also disturbed as it may take a long time to have answers of particular questions. This means that it is not easy to manage big data as well as presenting it in a manner that business leaders may understand and apply it. There can be an important effect if visual analytics are paired with big data. The other challenge is the way to access and analyze huge amounts of data in a faster manner and how to feature in quality of data. Effective data visualization should be able to make the viewer to consider the substance instead of the methodology, the design or even the technology of producing the graphic. It should also be effective in such a way that it does not distort what the data has to show (Love, 2008).

 

 

 

References

Tufte, E. R. (2006). The visual display of quantitative information. Cheshire, Conn: Graphics Press.

Pauwels, L. (2006). Visual cultures of science: Rethinking representational practices in knowledge building and science communication. Hanover, N.H. [u.a.: Dartmouth College Press [u.a..

Love, N. (2008). The data coach's guide to improving learning for all students: Unleashing the power of collaborative inquiry.