Northwind Traders

For this project, I had began first by formatting the data types and ensuring they are all set correctly.

As a next step I had went over the data to see what I could analyze and what are the insights that I could achieve from the data provided. Upon careful review I decided to showcase different screen for all the data I could analyze, so I was left with showcasing data on the following: Sales, Customer Insights, Product Performance, Employee Performance, and Shipping Details.

I first Started off by creating a the Sales Screen, where I had calculated the net sales, gross sales, total discount and total quantity sold. These measures would later help me in analyzing the performance of the business from different aspects. I also created a measure to showcase last years sales based on the date filter, which compares the current gross sales vs the previous year gross sales this would be beneficial to understand whether we are doing better since the last year or not. Additionally, an area chart was developed to showcase a daily overview on the sales on a daily aspect for each month. The total quantity sold chart helps us in analyzing whether there is a relationship between the quantity sold and gross sales. Finally the discount chart gives us an overview on the discounts for each month.

Moving onto the second screen which is the customer insights, I had created a created a bar chart and filtered on the top 5 customer to showcase the most important customers to the business, additionally the second bar chart is showing us the top 5 customers based on the quantity sold. Once again through this we could analyze to see whether our top customers by sales actually purchase the most quantity or not. As it is for any visualization of customers, I added a map showcasing our sales on every city. This could help us in viewing what areas we could work on better. Finally, a heatmap for the customers has been added to showcase whether the customer is doing well in gross sales, whether the quantity purchase is high, and if the total discount is high compared to other customers.

Now that we understood how our sales and customers are doing, its time to analyze our products to understand what is doing well and what should be discontinued. For the products screen, we had to main aspects through which we could analyze the data that are the product categories and the products themselves. I started by creating a column chart showing the gross sales for each category, moving forward I introduced a bar chart showing the top performers from our products, now that we know which of our products are doing so well it is only fair to also have a look at our low performing products to further investigate why this is the case. Finally, I noticed that some products have been discontinued, so I decided to show the sales for the discontinued products. To my luck, we notice that one of the top performers are actually being discontinued. Have I not showcased the discontinued products we would not know this.

For our fourth screen, it is now time to have a look at our employees and how well they are doing. Based on the employee selection, the employee gross sales, net sales, quantity sold, and total discount provided to customers will be shown. Along with this data, it is important to recognize our top performer therefore I had added the name of the top salesman along with his/her sales value. As we filter on our employee and select the dates, we find two bar chart that showcase which customers the employee is selling to along with the sales value to analyze the customer and employee sales relationship. The second visualization gives us on how well the select employee is selling based to our categories.

Last but now least, our screen is showing the shipper details. For this screen, I wanted to show a few for the business unit concerned with operations, I had created measures to showcase the average shipping time to achieve this I subtracted the order received date and the order ship date, also it is important to know whether the order is late or not, within the data set we have a required date field showcasing when the customer had requested the order to be shipped, I used a simple if function to check if the ship date is greater than the required date. Moving onto the visuals, I created a bar chart showing the total freight charges for each shipper, secondly we have a line chart showing the total number of late orders from each customer. The third visual is showing us further details on the shippers and the orders they have shipped, I added conditional formatting to this table to have it as a heatmap. Finally, I compared the average cost of shipping vs the average of the quantity for the shippers to show the relationship between the two.