Visit all my Power BI projects
Harnessing the capabilities of Power BI, I have developed extensive skills in data visualization, reporting, and analytics. My experience with Power BI includes:
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Interactive Dashboards: Creating dynamic and interactive dashboards that provide real-time insights into key metrics and business performance.
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Data Connectivity: Connecting to a wide variety of data sources, including databases, cloud services, and spreadsheets, to ensure comprehensive data integration.
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Advanced Visualizations: Designing sophisticated visualizations such as bar charts, pie charts, scatter plots, and more, to effectively communicate data stories.
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Data Modeling: Building complex data models that support comprehensive analysis and reporting, using Power Query and DAX (Data Analysis Expressions).
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Data Transformation: Cleaning and transforming data to ensure accuracy and relevance, leveraging Power Query for data preparation.
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Custom Measures and Calculations: Creating custom measures, calculated columns, and KPIs to provide deeper insights and support decision-making processes.
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Row-level Security (RLS): Implementing row-level security to ensure data security and compliance, providing access to the right data to the right people.
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Power BI Service: Publishing reports to Power BI Service, sharing insights with stakeholders, and setting up automatic data refreshes for up-to-date reporting.
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Storytelling with Data: Crafting compelling data stories that highlight key trends, patterns, and insights, making information easily understandable and actionable for stakeholders.
These skills enable me to leverage Power BI to its fullest potential, providing powerful and visually compelling analytics solutions that drive informed decision-making and strategic planning.
Wealth Distribution Analysis with Data from a British Bank
Project Overview
This project focuses on the analysis of wealth distribution using data obtained from a British bank, specifically across four provinces. After cleaning and transforming the data, it is employed to analyze wealth distribution across age groups, financial status, occupations, and gender.
Objective
To provide a comprehensive analysis of wealth distribution and deliver insights through an interactive dashboard, aimed at informing financial strategies and decisions.
Key Insights
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Age Groups:
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Assessed wealth distribution across different age cohorts to identify trends and financial behaviors.
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Financial Status:
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Examined the financial health and stability of individuals in different financial brackets.
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Occupations:
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Analyzed how wealth varies among different occupational groups, highlighting professions with higher or lower average wealth.
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Gender:
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Explored wealth distribution differences between genders to identify any disparities.
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Data Visualization
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Wealth Distribution Across Age Groups:
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Interactive visualizations display wealth trends across various age cohorts, providing insights into financial behaviors at different life stages.
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Financial Status Analysis:
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Detailed charts and graphs illustrate the financial health and stability of individuals across various financial brackets.
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Occupational Wealth Distribution:
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Visual representations highlight how wealth varies among different occupations, shedding light on economic disparities.
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Gender-Based Wealth Distribution:
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Visuals explore the differences in wealth distribution between genders, highlighting any existing disparities.
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Conclusion
The wealth distribution analysis project provides valuable insights into the financial dynamics within the four provinces. By examining wealth distribution across age groups, financial status, occupations, and gender, the interactive dashboard offers a clear and user-friendly view of the data, aiding stakeholders in making informed financial decisions.
Euro Exchange Rates Analysis with Power BI
Project Overview
This Power BI project focuses on the analysis of Euro exchange rates across major economies worldwide. By visualizing and examining the data, the project highlights key insights into the economic dynamics and creditor-debtor relationships among European nations, with a particular emphasis on Japan, France, and Germany.
Objective
To provide a comprehensive analysis of Euro exchange rates and identify the primary creditors and high-risk nations within the European economic landscape. The project aims to enhance understanding of the financial stability and risk profiles of various countries.
Key Insights
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Primary Creditors:
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Japan, France, and Germany emerge as the main creditors, extending significant financial resources to other European nations. This indicates their robust economic positions and influence within the Eurozone.
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Risk Assessment:
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Countries are color-coded based on their risk levels, with gray shades indicating low-risk and stable nations. In contrast, yellow and orange shades highlight high-risk countries with potential economic instability. This visual representation allows for quick identification of regions requiring closer financial scrutiny.
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Data Visualization
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Euro Exchange Rates: Interactive visualizations display the exchange rates of the Euro against major currencies, providing insights into trends and fluctuations.
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Risk Map: A geographic map color-coded with shades of gray, yellow, and orange to represent the risk levels of different countries. This map effectively communicates the economic stability and potential risks associated with each nation.
Conclusion
The Euro exchange rates analysis project in Power BI offers valuable insights into the financial interrelationships within Europe. By identifying key creditor nations and assessing the risk profiles of various countries, the project provides a comprehensive understanding of the economic landscape, aiding in informed decision-making for stakeholders.