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Analysing the Superstore Sales Dataset Using Tableau | Tableau Project Help, Tableau Assignment Help


Analysing the Superstore Sales Dataset from different aspects so as to derive meaningful business insights which in turn help in better decisions making and growth of the business

Here we are going to consider the Sample Superstore Sales data to build our analysis in TABLEAU in order to draw some meaningful insights, so that we can add value to our business. (Tableau has been recognized as one of the Top Analytical tools by Gartner Survey over the years)

This data is about the Superstore sales dealing in various categories of products which are further divided into various subcategories.

Data Set Size- 6.5Mb

No. of Rows - 51290

No. of Columns - 20

The reason for choosing this particular dataset the amount of information in terms of variety of columns and the records presenting this presents a great opportunity for deriving number of meaningful insights that can help in the growth of Superstore Inc.

As can be seen from the above dataset snip it contains –



Bar Graph - To get a glimpse of the sales of various subcategories across different categories

CONCLUSION (Category wise) -

1) Furniture-

Chairs has maximum share in the sales, but there is not much difference between the Chairs and the Book cases.

2) Office Supplies-

Storage has maximum share in the sales. Additionally, around 50% of the share in Office supplies is accounted by Storage and Appliances. There is a huge gap in the contribution between the first Two and the others

3) Technology-

Phones has maximum share in the sales and followed by the Copiers- which together account for 50% of total Technology sales.


Quadrant Analysis - Here we will try to find out whether the discounts given on various products is really a profitable deal.

By doing the Quadrant analysis, the products are segregated into four quadrants, according to the Average Discount and Profit Ratio (Profit per unit of sale)


The products falling into Upper Right Quadrant are- Higher Discount and High Profit Ratio

The products falling into Upper Left Quadrant are- Lower Discount and High Profit Ratio

The products falling into Lower Right Quadrant are- Higher Discount and Low Profit Ratio

The products falling into Lower Left Quadrant are- Lower Discount and Low Profit Ratio

So, we need to concentrate on those particular products which are falling into lower right quadrant- where the discounts are high but the profits on those particular products are low- Therefore it is not a favourable condition to give discounts on these products


Pareto Chart - Here we will identify those products which are contributing the most to our total sales.


By drawing the Two -coloured Pareto chart we get to know how many products are contributing to the 75% of the total sales. These products can easily be identified and option to provide offers to these products can be explored.

Further it also helps in identification of the products which are contributing very less share in the total sales. These products needs’ further concentration and identify whether it would be a feasible option to promote these products.


Stacked Chart - Here we will try to understand that how much time each subcategory takes to deliver from the day of Order Date. We will analyse the percentage of orders delivered on time and late within each subcategory. The Standard delivery time is 3 days from the date Order is placed


The Orange portion in each graph shows the Percentage of orders which takes more than 3 days to be delivered within each Sub category. It can be seen from our analysis that within each subcategory the percentage of orders delivered beyond the 3 days is almost same that is around 30%.

So, we can conclude that the products being delivered late is not due to any particular product, so there might be a bigger issue with overall supply chain that is being currently followed to Ship the Products.

This study will help the Store Management to do the Root Cause Analysis for this huge gap & take necessary decision & overcome this delay


Line Diagram - Data can be interpreted in several ways as per the specific requirement and can be used to gain further insights to get the real picture of the current situation.

Here we will be going to get a picture of how good are bad the various Regions are performing on the Sales front.


Here we can easily view that there is a huge gap Between the Central and the south region

The Sales in the Central region is the highest in all the Years under consideration.

Moreover, as the Slope of the central region is upward sloping, so we can conclude that sales in the Central region is increasing overtime. But as far as the other regions are concerned, the sales is either increasing at a very slow pace or either stagnated, particularly for the Caribbean and Canada Region


At last we are going to build the Dashboard by combing specific sheets to get a clear picture out of our analysis.

From the above analysis and report, it is very clear that how the Data Analysis and Business Intelligence helps us to find the answers to various business problems, that can provide the competitive edge to any business in order to understand the current business situation in much better and accordingly formulating the specific policies in a directional manner, rather than blindly following the business operations.

So, it can be concluded that DATA ACTS AS an OIL for running the smooth business operations- in this 21st Century. It depends on the expertise and knowledge how to filter that data so as to remove the unwanted impurities like in oil- so that the desired output can be generated which can help to run various Business Operations more efficiently and effectively.

Part 3



Tableau is a powerful data visualization tool used in the Data Analytics and Business Intelligence Industry. It helps in simplifying raw data which in turn can be easily turned into an understandable format., to gain meaningful insights out of the data

The great thing about tableau is its user-friendliness it offers to the users for various analysis. By using Tableau, even a non-technical user can create a customized dashboard. The best feature Tableau are

  • Data Blending

  • Real time analysis

  • Collaboration of data

Over the years the tool has attracted the attention of people from all sectors such as business, researchers, different industries, etc.

Moreover, to promote the product within educational institutions, students at college level, it offers a Tableau student version which is free for the students up to a period of one year


1) Tableau is an expensive software as compared to its competitors

2) Difficult to learn as compared to Power BI

3) Inflexible Pricing

Contact Us to get any help related to tableau visualization or tableau data analysis with dashboard at:

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