Data Visualization and its different types From the time immemorial man invented drawing and the script, we have learnt that a photo is worth thousand words. The use of this unique quantity may be in simple terms allegorical and figurative, but nothing reinforces this factor more than a new technological know-how (or tool, if you like) that seems to be turning into vital for businesses: Data Visualization.
Data Visualization is pretty a self-explanatory term. At its simplest, it is all about visualizing data. But what information is visualized, why, and how? And where does the data that is visualized come from? These questions take a seat at the core of this activity. We can apprehend Data Visualization as the illustration or graphic representation of the data that groups generate from a wide variety of sources. And these sources should be without a doubt somewhere from the Net, such as the social media, for instance. Big Data, the buzzword in the world of technology, turns up colossal amounts of data, all of which can be of widespread use for businesses, however only if they are explained and represented meaningfully in a visual format. This is what Data Visualization genuinely is. A statistics visualizer makes use of strategies such as graphs, charts, maps and so on, to explain business data. At the coronary heart of Data Visualization lies the concept that information should not only be in a palatable manner, but should also supply companies the perspicacity to enable commercial enterprise decisions. This ability that Data Visualization is no longer only about presentation, however also about evaluation and insightfulness.
Now, the different types of data visualization How does Data Visualization go about doing its job of making data look attractive and useful? Are there different types of Data Visualization? Yes, and these are a few of them: Column chart: This is mainly about using columns to represent what is contained in data. The vertical columns are drawn to help understand the difference between various units of data. Column Data is useful in helping explain medium to small data. Line chart: Line charts are considered a vital type of Data Visualization. Why? Simply because they can show how and to what extent data varied over a specified point of time. This is an important tool for analysis that helps to understand the degree of change of many important units.
Bar chart: Bar charts are a popular form of Data Visualization tools, because they help to understand data better by enabling them to be read using different axes. Another advantage bar charts have over column charts is that they can analyze larger amounts of data. Pie chart: As indicated in the name, a pie chart represents data in a circular figure. This kind of statistical graphic divides data into slices, each of which can explain a specified value in numbers. Pie charts are of enormous value in helping to understand how subsets or components contribute to the whole. A pie chart is useful in describing hierarchies of data. Scatter plot: Want to describe two variables of a data set in the form of points to understand how they relate to each other? You could use scatter plots to do so. The way in which the data points are distributed explains how they interact with each other. This is useful when huge volumes of data has to be analyzed. Bubble chart: One can describe multitudes of data of a scatter plot in the form of bubbles. This is suited when limited amounts of data are being analyzed. What we have described here is a small set of the various Data Visualization types. You can explore more about this fascinating area of study by looking at some of our online courses on Data Visualization. We are confident that you will find them very interesting and fun to learn from! We would also like to understand if you found this blog informative. Please let us know your thoughts by writing to us.