Data visualization can be described as ‘the presentation of data either in graphical or pictures format to the users’. Data visualization allows decision makers to view analytics visually presented, so that they can understand difficult concepts or to recognize new patterns. Making visualization interactive, entrepreneurs can take their concept to the next level by using this technology to transform data into graphs and charts for more details. There are various data visualization techniques used in various industries.
Data Visualization For Big Data
Many businesses that handle big data considers data visualization as a wise investment. With big data, data visualization is a potentially great opportunity, however, many retail banks faces difficulties when they want to find value for their big data investment. Instead of using spreadsheets or reports to visualize the data to our brains, it is easy to use charts and graphs to grasp the data easily. In simple words, data visualization is the easiest and quickest way to bring concepts in a universally acceptable way. One can also make little adjustments and make some experiments to provide effective data visuals.
Data visualization facilitates businesses in identifying areas which needs improvement or attention, clarifies which aspects are influencing customer behavior, helps businesses understand the placement of variety of products, and also predicts sales sizes. Data visualization have a great impact on corporate world and have a great future ahead. It is said that, a picture can speak a thousand words; the same applies for data visualization too, especially, when it comes to trying to understand and relate the organization data. There are various data visualization techniques and tips available to create some meaningful visuals of a company’s data.
Techniques Of Data Visualization
The size of data and composition plays a major role while selecting graphs and pictures to represent your data. Data visualization techniques works similar for both big data and traditional data. Line Charts, Pie Charts, Bar Charts, and Heat Maps are some techniques used. Line Charts, enables to observe the behavior of more than one variable over the time and also identifies various trends. Companies can use this data visualization technique for tracking their big data. Pie Charts can be used to observe customer segments or market shares or any other component in whole. The only difference depends on the sources from where companies takes raw data for analysis. Bar Charts allows companies to compare different variables values. Usually, companies uses traditional business intelligence to analyze their sales of each category independently, or the costs of marketing, promotions by various channels and so on. Companies while analyzing big data, look at their websites pages for visitors engagement. Heat Maps uses colors to present data, usually found on excel sheets highlighting sales. The highlighting will generally be best performing sales store with green and worst performing store in red color