Analyzing a Supermarket Sales Data Set Using Power BI

I’m thrilled to announce a significant achievement in my exploration of data analytics: the successful completion of a project utilizing Power BI. This endeavor proved to be not only enlightening but also incredibly gratifying. I would like to guide you through the journey.

Here are the objectives I aimed to accomplish:

1. Determining the Total Sales.
2. Identifying the City with the highest amount of Sales.
3. Pinpointing the item with the highest sales across all branches.
4. What is the preferred method of payment across all branches.
5. Identifying what payment method was used more in each branches.
6. What’s the Total quantity of items sold?
7. What month had the highest sales?

Objectives
1. Clean dataset and build a simple Dashboards using power BI.

2. Using a textbox, add Conclusion and recommendations in your dashboard.

Step 1: Data Cleaning and Transformation

I began the project by getting the data from the source and loading it to Power Query for transformation. I cleaned the data by unpivoting the column necessary based on the structure of the dataset. I then added the conditional columns that would help with the computation of the key metrics. Once I was satisfied that the data was clean I loaded it into Power BI.

Step 2: Building Visualizations

Visualization serves as the channel that links unprocessed data to valuable insights. I utilized the capabilities of Power BI to craft an array of visual representations, encompassing cards, tables, and charts, in order to breathe vitality into the data.

Step 3: Providing Recommendations

Accompanying the answers, I offered actionable recommendations based on the analysis. Recommendations serve as guiding lights, illuminating opportunities for improvement and further exploration.

Below is the Report of the analysis answering the questions posed at the beginning of this article.

Report Analysis

1. Total Sales across all branches was $322,966.75.
2. City with the highest amount of Sales is Naypyitaw with $110,568.71.
3. Item with the highest sales across all branches is Food and Beverages with total sales of $56,144.84.
4. Preferred method of payment across all branches is cash payment with a total of $112,206 which is 34.74% of the total sales made.
5. Payment method was used more in each branches are Cash Payment at Naypyitaw, Credit Card payment method at Yangon and Mandalay branches respectively.
6. Total quantity of items sold across all branches is 5,510.
7. The month January had the highest sales with a sum of sales of $166,291.

Recommendation
My recommendation will be to focus on Naypyitaw as a key market for further growth and expansion efforts, particularly in the Food and beverages product line.

This could involve increasing marketing efforts, introducing new products or optimizing supply chain logistics to ensure continued success and potentially further increase the market share in Naypyitaw.

Additionally, explore strategies to bridge the gap with Mandalay, which has the lowest Sum of Total sales, could also be beneficial to achieve more balanced regional performance.

Consider offering bundled deals that include discounts or special offers when customers use E-wallet or Credit card payments to encourage customers on using such payment method and limit the use of Physical cash for the safety of customers.

If you’re interested in data analytics or have any questions about the process, please feel free to reach out. Let’s continue our collective journey of learning and growth. 🚀📊

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