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https://github.com/rakumar99/power-bi-projects

This repository contains various power bi projects and dashboards of Humaan Resources , Financial Analysis using Power BI Desktop.
https://github.com/rakumar99/power-bi-projects

dashboards data-analysis data-visualization databases datacleaning datamodeling etl powerbi powerquery reports

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This repository contains various power bi projects and dashboards of Humaan Resources , Financial Analysis using Power BI Desktop.

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README 

        
# Power-BI-Projects



Welcome to my repository showcasing various Power BI projects. Each project highlights my expertise in creating data-driven insights through intuitive dashboards and reports, demonstrating my ability to transform raw data into meaningful visualizations for business intelligence



Power BI:



Power BI is a versatile analytics tool developed by Microsoft that enables users to:



Connect to a wide range of data sources,Clean and transform data for analysis, Visualize data using interactive dashboards and reports and also we can Share insights effortlessly with others through cloud services.



Power BI’s powerful visualizations and user-friendly interface make it ideal for crafting impactful and interactive reports.



Projects in This Repository:



Project 1. Human Resources Reports/Dashboards:


   

Dashboard 1 : HR Report by Salary and Employee Count

Objective: This dashboard presents a detailed view of employee count and salary distribution across various departments, job classifications, and business units.



Key Insights:



Visual representation of salary disparities across different business units (e.g., Seattle, New York City, Los Angeles).

Breakdown of employee count by job type (Full Time, Part Time) and job classification (White Collar, Other).

Interactive filters to drill down by department (e.g., Legal, Accounting, HR) and group (Group A, B, C) for a more customized analysis.



Dashboard 2: HR Report by Averages and Performance



Objective: This dashboard provides a high-level view of HR data, focusing on average salary, years in the current role, and performance ratings.



Key Insights:



Average salary comparison across departments, groups, and gender.

Employee tenure analysis, showing the average number of years employees have been in their current role and since their last promotion.

Performance ratings (Outstanding, Excellent, Good) and how they correlate with other metrics like job involvement and satisfaction.



Dashboard 3: HR Report by Business Units and Regions



Objective: This dashboard visualizes HR metrics across different business units and geographic regions.



Key Insights:



Employee distribution and salary trends segmented by business units (e.g., Seattle, Los Angeles, New York City).

Performance and satisfaction analysis by business unit and region, helping identify regional disparities in HR metrics.

Use of filters to break down the data by job type, education level, and work-life balance ratings.



Project 2. Financial Analysis Report: 



Project Overview:



The Financial Performance Dashboard consolidates multiple critical reports into a single interactive view, enabling users to explore the following metrics:



Total Sales by Country: Visualizes sales distribution across various countries, highlighting the top-performing regions with interactive visuals.



Discounts Impact: Tracks sales influenced by discounts, allowing businesses to see the correlation between applied discounts and total revenue. Users can filter to analyze specific discount categories and their contribution to sales.



COGS and Profit Margins: The dashboard calculates and displays Cost of Goods Sold (COGS), along with profit margins across different segments, products, and regions. The analysis helps to identify profitable products or services by comparing COGS with total revenue.



Sales by Segments and Products: Offers an in-depth look at how different customer segments (e.g., retail, corporate) and products contribute to overall sales and profitability. The dashboard provides insights into which segments and products are driving revenue growth.



Monthly Sales Trends: Displays sales performance by month, identifying seasonal trends and peak periods for certain products or regions. The time-series view allows users to analyze how sales fluctuate over time, making it easy to spot trends and anomalies.



The dashboard integrates all these components into a single, user-friendly interface, enabling decision-makers to interact with the data through dynamic filters and drill-downs. This allows for a detailed and customized analysis based on specific business needs.



Project 3: Product Analysis Dashboard



The Product Analysis Dashboard integrates multiple aspects of product purchasing data into a single view, allowing users to explore.



Total Purchases and Quantity Purchased: Visualizes the overall purchases and total quantities bought across different time periods.



Purchases by Color: Allows users to filter and analyze the data by product color, offering insights into color-specific purchasing trends over the years or quarters.



Purchases by Year and Quarter: Displays purchasing trends across different years and quarters, helping businesses identify seasonality effects on purchasing behavior.



Supplier Analysis: Highlights purchases segmented by supplier, providing a comprehensive view of supplier performance and contribution to total purchases.



This dashboard allows for easy filtering and drill-downs, enabling detailed, customized analysis of the purchasing data based on user preferences.



Tools & Technologies Used;



Power BI Desktop: For designing dashboards and reports.



DAX (Data Analysis Expressions): To implement custom calculations and measures.



Power Query: To transform and clean data for analysis.



Data Sources: A range of sources including Excel, CSV, SQL Server, and APIs.



Project Overview:



Each project includes:



A PBIX file (Power BI Desktop file) containing the full report and dashboard.

Screenshots or GIFs demonstrating key visuals.

Documentation explaining data sources, key performance indicators (KPIs), and insights from the analysis.