As an aspiring data analyst this is my first project. As part of this project I have analysed the sales and order data for Northwind Traders, a fictitious gourmet food supplier. The data encompassed information on customers, products, orders, shippers, and employees.

The goal was to analyze noticeable sales trends over time, identify top-selling and bottom-selling products, determine key customers, and examine shipping costs across providers.

Steps fallowed:

As a separate Calendar table was not available, I created a calendar table using the CALENDAR function. While it is advisable to have a dedicated calendar table for complex time intelligence functions, this approach allows for basic date-related analysis.

To enhance the report's aesthetics and structure, I utilized PowerPoint for creating the background. The report includes page navigation, enabling seamless interaction between different pages. Each page is dedicated to analyzing specific aspects such as sales, products, customers, employees, and shippers. This allows for in-depth analysis and a comprehensive understanding of each area.

Sales Trends:

In Sales page I have used the two slicers one for country and other for year. Country's filter interaction is appicable to only sales page where as I have given filtering of year slicer for all pages. We have data for 2013,2014,2015 in which complete year data is available for 2014 and may 2015 data is incomplete. Therefore I have used the month(MOM revenue trends) and quarter in charts and given filter option to the years.

The sales show improvement year by year, indicating a positive growth trend. Additionally, during the festive season, particularly in December and January, the sales show a significant increase. This suggests that the holiday season has a positive impact on sales for Northwind Traders. We can see larger revenue contribution from North America compared to other regions.

Proucts and Category:

On this page, I have dedicated my analysis to examining each product and its revenue share. To display dynamic values in the visualizations and headings, I have utilized the SELECTEDVALUE function. To analyse the discontinued products I have used the pie chart(around 9% discontinued). Matrix is used display top 5 and bottom 5 selling products based on the revenue.

Customers:

On this page, I have focused my analysis on examining customers. I have utilized a matrix visualization to identify the top 5 repeat customers, as well as the top 5 and bottom 5 customers based on revenue. This provides a clear understanding of the most valuable customers and those who may require further attention.

To analyze the customer distribution across regions, I have employed a map visualization. This allows for a geographical representation of customer share, providing insights into which regions have the highest customer concentration.

The interaction on this page is dynamic, meaning that data will be displayed specifically for the selected year. This enables a more targeted analysis of customer behavior and trends over time. Furthermore, users can select individual customers to gain deeper insights into their specific purchasing patterns and behavior.

Employee and Shippers:

This page analyzes the top shippers based on revenue, average shipping cost per order, and orders handled. It provides overall and year-wise trends. Speedy Express stands out for offering lower shipping costs per order. Tooltips offer additional information about each shipper, including on-time delivery, late delivery, average shipping days, total revenue, and orders handled. Analyzing average shipping costs helps identify cost-saving opportunities, while examining orders handled helps evaluate efficiency and capacity. This analysis supports informed decisions on shipping strategies and cost optimization.

This page also analyzes employee performance, revenue contribution, and the number of orders handled. A sunburst visualization is used to examine employees by region, and tooltips are included to display employee titles. This analysis provides insights into employee productivity, revenue impact, regional distribution, and facilitates effective resource allocation.