Descriptive Analytics is one of the core components of any analysis life-cycle pertaining to a data science project or even specific research. Data aggregation, summarization and visualization are some of the main pillars supporting this area of data analysis. Since the days of traditional Business Intelligence to even in this age of Artificial Intelligence, Data Visualization has been a powerful tool and has been widely adopted by organizations owing to its effectiveness in abstracting out the right information, understanding and interpreting results clearly and easily. However, dealing with multi-dimensional datasets with typically more than two attributes start causing problems, since our medium of data analysis and communication is typically restricted to two dimensions. In this article, we will explore some effective strategies of visualizing data in multiple dimensions (ranging from 1-D up to 6-D).


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This article is related to

Data Visualization,2018,Multi Dimensional Data