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https://github.com/shivam5509/power-bi-project

Expert in creating interactive dashboards and reports using Power BI, utilizing 10+ visual tools like cards, slicers, and charts. Skilled in cleaning and transforming large datasets with Power Query Editor. Proficient in advanced DAX functions (SUMX, FILTER, CALCULATE) to derive insights and drive data-driven decisions.
https://github.com/shivam5509/power-bi-project

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Expert in creating interactive dashboards and reports using Power BI, utilizing 10+ visual tools like cards, slicers, and charts. Skilled in cleaning and transforming large datasets with Power Query Editor. Proficient in advanced DAX functions (SUMX, FILTER, CALCULATE) to derive insights and drive data-driven decisions.

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# Power-BI-project

Expert in creating interactive dashboards and reports using Power BI, utilizing 10+ visual tools like cards, slicers, and charts. Skilled in cleaning and transforming large datasets with Power Query Editor. Proficient in advanced DAX functions (SUMX, FILTER, CALCULATE) to derive insights and drive data-driven decisions.

# Blinkit Sales Dashboard



## Overview

This **Blinkit Sales Dashboard** was developed using **Power BI** to provide a comprehensive analysis of Blinkit's sales data. The dashboard offers valuable insights into key sales metrics, helping stakeholders make data-driven decisions to enhance business performance.



## Features

- **Interactive dashboard** with 10+ visual tools including:

  - Cards

  - Slicers

  - Bar charts

  - Line charts

  - Donut charts

- Processed and transformed **50,000+ rows** of sales data using **Power Query Editor**.

- Improved data accuracy by **20%** through data cleaning and transformation.

- Applied advanced **DAX functions** such as:

  - **SUMX**

  - **FILTER**

  - **CALCULATE**

- Provided actionable insights, resulting in a **15% increase** in data insights and a **10% growth** in revenue.



## Tools & Technologies

- **Power BI**

- **Power Query Editor**

- **DAX (Data Analysis Expressions)**



## Project Highlights

- The dashboard tracks important sales KPIs such as total revenue, product performance, and sales trends over time.

- Offers interactive filtering through slicers to allow users to drill down into specific data points for deeper analysis.

- The use of advanced DAX calculations enables more detailed data exploration, improving decision-making for the sales team.



# IPL Games Dashboard



## Overview

The **IPL Games Dashboard** is a comprehensive analysis tool built using **Power BI**, designed to provide insights into the performance of IPL teams, players, and matches across **15 seasons**. This project incorporates over **1000 match statistics** to visualize key trends and metrics in the Indian Premier League (IPL), aiding stakeholders in making data-driven decisions.



## Features

- **Interactive dashboard** with **10+ visual tools** including:

  - Cards for key metrics like total runs, wickets, and strike rates.

  - Bar charts to compare team performance.

  - Donut charts to visualize player contributions.

  - Slicers for easy filtering by team, season, and match type.

- Analyzed **1000+ matches** and transformed **50,000+ rows** of data.

- Applied advanced **DAX functions** like **SUMX**, **FILTER**, and **CALCULATE** for complex calculations.

- Cleaned and processed raw data using **Power Query Editor**, improving data accuracy.

- Enhanced **25% improvement** in data-driven decision-making for IPL analysts and stakeholders.



## Tools & Technologies

- **Power BI**

- **Power Query Editor**

- **DAX (Data Analysis Expressions)**



## Project Highlights

- Tracks KPIs such as total runs, wickets, win/loss ratios, and player statistics.

- Visualizes team standings and season-wise comparisons across 15 IPL seasons.

- Interactive filtering capabilities allow for detailed analysis by team, season, and player.

- Enabled IPL teams and analysts to monitor performance and identify key trends to improve future strategies.



# Olympics Games Analysis Dashboard



## Overview

The **Olympics Games Analysis Dashboard** is an interactive data visualization project built using **Power BI**. It provides in-depth insights into Olympic Games performances across various years, including medal counts, athlete achievements, and country-specific data. The dashboard allows users to explore data using intuitive visual tools, offering a comprehensive understanding of trends in the Olympic Games.



## Key Features

- **Data Visualization**:

  - Visual tools such as bar charts, line charts, and maps to display medal counts, event-wise distribution, and athlete statistics.

  - Slicers and filters to easily navigate between countries, sports, events, and years.

  

- **Data Insights**:

  - Analyze performance across multiple Olympic seasons, identifying top-performing countries and athletes.

  - Explore event-specific data, such as medal counts per sport, gender-based participation, and country dominance in particular disciplines.

  

- **Interactive Experience**:

  - Users can interact with the dashboard to filter data by athlete, country, year, or event, providing dynamic insights for a better understanding of Olympic trends.

  

- **Powerful Reporting**:

  - Historical comparisons of country rankings, top medal winners, and overall participation over time.

  - Detailed drill-downs into individual athlete performances and their contributions to country rankings.



## Tools & Technologies

- **Power BI**

- **Power Query Editor**

- **DAX (Data Analysis Expressions)**



## Dashboard Highlights

- Tracks performance data across multiple Olympic seasons.

- Provides detailed analysis of medals by country, event, and year.

- Interactive slicers to filter data by sport, gender, athlete, and medal type.



## How to Use

1. Clone the repository.

2. Open the **.pbix** file in Power BI Desktop.

3. Explore the dashboard and interact with the visualizations using slicers and filters.



## Contact

For any inquiries or feedback, feel free to reach out to **[Shivam Raj]** at **[shivamraj576009@gamil.com]**.