Dahel Consultant and Techies: Sales Analysis; A deep dive into Pie-Day Sales data, aimed at extracting valuable insights to enhance strategic decision-making. (The picture below is gotten from The Guardian Nigeria News Website).
Disclaimer: This is not a real company as we know this is a dataset compiled by Dahel Consultant Techies for Internship purposes.
This is Pie sales performance analysis. It is done by analyzing data from the Pie Day table which comprises of Order NO Order Date column, Month/Yr column, Day of Week column, Pie Flavor column, Quantity column, Cost column, Slice Or Whole Pie column, Pre-Order/In-Store Purchase column, Organic? column. I used Excel to get an overview of the dataset before importing it into Power BI where the actual analysis was carried out.
The goal of this analysis is to know:
- What was the total number of orders?
- The total number of pies produced?
- Which flavor did the customer order most?
- Which means did the customer order for pie the most (pre order or in store purchase)?
- What is the relationship between the cost and quantity.
- What is the cost per year and month?
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Power BI concepts like:
- Creating key performance indicators (KPIs) and other business calculations
- Data Modelling,
- Measures,
- Filters,
- Tooltips,
- Page buttons,
- Data visualization
The dataset for the work is gotten from Dahel Consultant Techies. It consists of 2,774 records and 10 fields of data. I studied the dataset well to gain proper insight into the dataset. You can find a link to download the dataset here:
Step 1:
- After downloading the dataset, I imported it into POWERBI.
Step 2:
- It loaded the dataset authomatically in Power Query Editor but there was no cleaning needed because it was already a cleaned data.
Step 3:
- For the column cost I assumed it was the cost of production because I wasn’t sure if It was the selling price or the cost of production
Step 4:
- After checking the columns, it was loaded into POWERBI for visualization.
Several expressions and functions were made to arrive at the desired KPI or Metrics. I arrived at a report with a single dashboard consisting of different visuals such as bar chart, doughnut chart, line chart, slicer, and KPIs, giving the summary of the insights gained into the company's performance.
The dashboard conveys information about the following key areas:
- Total number of orders
- The total number of pies produced
- Flavor with the highest order
- Means of order (pre order or in store purchase)
- Relationship between the cost and quantity
- The total cost per year and month
Summary of the insights gained into the chess Game performance:
- A total of 2,773 orders were placed between 1st of June, 2019 – 1st of November 2021.
- A total of 8333 pie was produced during that period. The total cost it took to produce the 8333 pie was $96,922.50
- 51.21% of the pie produced was pre-order while 48.79% of the pie were purchased in store.
- There were over 6 flavors of pie and the Apple flavor had the highest cost of production followed by Strawberry Rhubarb
- About 52.51% of pie ordered where whole pie and 47.49% were sliced.
- The higher the quantity, the higher the cost.
- Due to the uncertainty whether the cost provided is the selling price or the cost of production much recommendation can't really be given.
- There’s no way to know which pie flavor generates more profit or the one with the most profit.
- The Apple flavor is the most ordered pie and it should always be made available.
- The PIE should still be made available as both pre-order and in store purchase because there’s no much difference in how customer choose to purchase their price.
- Both whole pie and sliced pie should also made available since customers placed other for both and the margin between both isn’t much. About 52.51% of pie ordered where whole pie and 47.49% were sliced.
I am open for entry-level to mid_level data analyst role.