This project uses Power BI to analyze sales methods, regional and provincial sales, and category performance, aiming to deliver insights and support a deeper understanding of the company’s overall performance for informed decision-making and strategic planning.
Sales Data: The data source is "Excel files" containing detailed records of each sale made by the company.
- Excel
- Download here
- Powwer Query - data cleaning and merging
- Power BI - Creating reports
In the initial data preparation phase, we performed the folloqing task;
- Data Loading and inspection
- Handling missing values
- Data Cleaning and formatting
Exloring Data Sales to answer key question, such as;
Here are 5 key questions this Power BI project aims to answer:
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Which sales methods generate the highest revenue and customer engagement?
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How does sales performance vary across different regions?
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Which product categories contribute most to overall sales?
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What are the sales trends across individual provinces?
Include somes interesting code/feautes worked with
Xlookup Power Query Dax Functions for new measure
The analysis of results are summarized as follows:
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Online sales account for the majority of revenue.
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Electronics and home appliances top the list.
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Urban areas show higher purchasing activity.
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Regional differences highlight market strength in the South.
Based on the analysis , we recommend the following actions:
- Invest more in online sales channels to maximize revenue and customer reach.
- Strengthen marketing efforts in underperforming regions to balance sales distribution.
- Expand inventory and promotion of high-performing categories like electronics and home appliances.
- Develop region-specific sales strategies based on provincial trends and seasonal patterns.
A key limitation is the removal of zero values from the dataset to avoid distortion in analysis and accuracy. This may lead to the exclusion of low-activity areas or products, potentially affecting a full representation of sales performance.
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