Sales Analysis and Performance of Super Store Using Qlik GeoAnalytics

Data analytics is the science of predicting the future trends that support the study of gift information and past information that create inroads into the retail sector. Massive information analytics will offer insights into rather more than simply inventory levels and also the quality of various products. So as to create the simulation insensitive against short transient changes, a longitudinal analysis ought to be applied, to boot to the common crosswise analysis. For this purpose, we make use of Qlik Sense, Tableau, Python, R language to visualize the behavior of the sales data of a superstore which varies with time. While Qlik Sense and Tableau are the tools used for data visualization purpose, Python and R language are the programming languages used to draw patterns by coding. This paper also depicts the basic differences between the four tools used for data visualization. This paper proposes a Qlik Sense-based solution for the mentioned problem definition in the field of data analytics. Data patterns and trends are observed to draw the conclusions on the sales. As the major motto of retailer is to make profits by selling the products, there is a need for him to understand the data variations with the change in time, climate, regions, and customer’s interest. Thus to make his work easier, will use the resulted visualizations formed out of the sales data. Hence, this paper provides efficient ways of analyzing the sales data of a superstore, finding the reasons for the increase and decrease in the sales, controlling product imports, and attaining a profitable business.