ANALYSIS OF SUPERSTORE SALES DATASET USING EXCEL
Excel as its well known, is a primary tool for solving data with minimal analysis which is widely accepted by order data processing formula with more complex insight. It is designed as an explanatory tool, therefore creating charts in excel gives not just the reader but also the facilitator deeper understanding of our data. One of the significance of excel is that after analyzing the data, further questions and deep insights from the data; we can present our findings by stating a story. More so, technicality of excel gives it a more acceptability by organizations and establishments of various field like; the banking sector, the security sector, real estate, education sector etc to break down complex and rigorous data for better understanding.
In this article, I made use of Superstore Sales data set which was gotten at about four (4) years ago. You can view my story on excel since the data is in a text(CSV).
After; exploring, observing and analyzing the given data I was able to come up with the following conclusion.
> The city with the highest sales record as at the time of publishing this data set was New York City located in the state of New York in the Eastern Region with a postal code of 10024.
Using filter, I was able to see the city with the highest number of sales record at superstore sales.
> Also using the pivot table and chart, I was able to analyze the data to get the ship mode in order of use.
Using the ship mode and the count of ship date, I came to the conclusion that the standard class of ship mode was the most used and explored.
> To know the trend in sales using the product id and sum of sales in the data, I was able to detect that product id TEC-CO-10004722 was the trending product been sold with a sales volume of 61599.824 which is illustrated in the pivot chart below
The chart above shows us the top five (5) trending products with its various product id.
> In every merchandising business, it is of importance to find out which category of goods brings more return to the merchandising firm. And in our focus on this publication, superstore sales is not left out. Using the category and sum of sales, i discovered that furniture had the highest amount of sales category wise and is stated in the chart below.
Furniture had a total of 728658.5757 in sales volume gotten by superstore sales.
> For every purchase there must be some high level of patronage either by and individual or a group of people. In the chart below we shall see that Sean Miller with a total purchase volume of 25043.05 was the customer with the highest purchase.
In the illustration chart above, I made use of both the customers name and sum of sales.
> Some states had poor sales which might have been due to some factors which were not properly curtailed or lacked enough attention by the management and it happened that North Dakota was the most hit with a sales volume of 919.91 and its contained in the chart below.
This data was explored using states and volume of sum of sales.
> The order id with the most ship mode was CA-2018–100111 with the count of ship mode at 14 and its detailed in the chart below.
Regards.