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Projects in Power BI

Global Sales

Global Sales
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Context ​​

With the expansion of digital markets, understanding sales behavior in different regions is vital for sustainable growth. This project uses global data to analyze sales performance and profitability by continent and country, offering a strategic view of international operational efficiency.

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​Project objective​​

To present, in a clear and visual way:

• Annual and monthly sales volume, allowing the identification of growth trends;

• Geographic profitability, highlighting the most profitable markets. Supporting expansion decisions and resource allocation in global markets.

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​​Key Analytics

  • Sales Performance by Geography: A visual that uses maps and bar charts to identify which countries and continents lead in revenue, making it easier to visualize the dominance of the North American market;

  • Monthly Sales and Profit Evolution: A line graph that monitors financial health over time, helping to detect seasonality and demand peaks.

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Tool used​

  • Power BI

  • Power Query (Geographic data processing and field translation)

  • Data Modeling

  • Data Visualization (ArcGIS Maps and Trend Charts).

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​Project highlights​

  • Visual Standardization: Use of institutional color palette (Purple/Dark) to facilitate readability.

  • Clean and Organized Design: Layout focused on key KPIs (Sales, Profit, Margin).

  • Internationalization: Dashboard fully configured in English, simulating a multinational reporting environment.

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Conclusion​​

This project demonstrates the application of Power BI in consolidating complex global sales data. Through visual analysis, it is possible to identify that, although sales occur across multiple continents, the concentration of profit in specific regions requires localized marketing strategies to optimize overall results.

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Data source​

Global Sales Enterprise Dataset. (Structured database for analyzing the performance of international e-commerce).

HR People Analytics

HR People Analytics
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Context ​​

In the Human Resources sector, data analysis is fundamental for strategic people management. This project uses an HR dataset to explore demographic, financial, and performance indicators, allowing the identification of hiring patterns, salary disparities, and the operational health of the organization's human capital.

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​Project objective​​

Present, in a clear and visual way:

• The evolution of the workforce, identifying peaks and trends in hiring over the years;

• Salary efficiency by sector, comparing annual averages to ensure budget balance;

• The distribution of talent and performance, focusing on gender diversity and productivity by department.

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​Key Analytics​​

  • Hiring Trends by Year: Line chart that monitors company growth over time, highlighting periods of greatest expansion.

  • Average Annual Salary by Department: Bar chart that identifies personnel costs and professional development in each area.

  • Performance Distribution by Sector: Column chart that segments employee performance, helping to identify high-productivity departments.

  • Demographic Composition: Donut charts and icons that illustrate gender diversity and employee profiles.

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Tool used​

  • Power BI

  • Power Query (HR data processing and duplicate removal)

  • Data Modeling

  • Data Visualization (Trend Charts, Stacked Columns, and KPIs)

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​Project highlights​

  • Performance Analysis: Integration of performance scores with the departmental structure;

  • Visual Standardization: Clean and intuitive layout, with central KPIs (Salary, Total Employees, Absenteeism);

  • Focus on People Analytics: Dashboard geared towards HR managers and operations directors.

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Conclusion​​

This project demonstrates the application of Power BI in transforming raw HR data into business intelligence. Through visual analysis, it is possible to identify critical moments in company expansion and assess whether salary distribution is aligned with strategic objectives, optimizing decision-making regarding promotions and new hires.

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Data source​

Public sales dataset. (Kaggle – HRDataset_v14)

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