Power-BI_Projects

Power BI Portfolio Projects

Welcome to my personal Power BI portfolio repository! Here you will find a collection of Power BI projects and dashboards that demonstrate my skills and expertise in data visualization, business Intelligence and analytics using Power BI.

Project #1

Super Sales Insights - Dashboard

This Power BI project provides comprehensive insights into the sales data of a superstore. The analysis covers various aspects such as sales trends, product performance, customer segmentation, and geographical distribution. The interactive dashboards and visualizations make it easy to understand and derive actionable insights from the data.

Methodology

• Data Collection: Getting data from Kaggle.
• Data Cleaning and Preparation: Removing irrelevant and restructuring the dataset for easy analysis.
• Exploratory Data Analysis: Exploring and analyzing the cleaned data.
• Visualization and Reporting: Visually presenting data in the form of charts and graphs.
• Insights: Presenting observations from the analysis.

Analysis and Visualization

• Total Sales: What were the total sales for the company?
• Top Performing Market: Which market generated the most sales on average?
• Profit by Segment: What were the profits by segment? Identify the segment with the highest profit.

Tools

Kaggle, Power BI(DAX), Microsoft Excel

Project #2

TCS stocks market Insights - Dashboard

This Power BI project delves into the dynamic landscape of TCS stocks, offering a comprehensive analysis and visualization of key market indicators. The project encompasses a diverse range of charts and graphs, including time series charts tracking stock prices over various periods, key performance indicators (KPIs) highlighting crucial financial metrics, and comparative analyses against market benchmarks. Through interactive features and filters, users can explore trends, volatility, and factors influencing TCS stock performance. This project provides investors and stakeholders with actionable insights for informed decision-making in the dynamic world of stock markets. 📊📈

Dataset:

The dataset for this project comprises historical data on TCS stocks, encompassing daily stock prices, trading volumes, financial indicators, and relevant market data. The dataset is collected from reliable financial sources, ensuring accuracy and completeness for meaningful analysis.

Methodology

Data preparation involves cleaning, transforming, and organizing the dataset. Key tasks include handling missing values, converting data types, and structuring the data for effective analysis. Time-based aggregations and calculations are applied to unveil trends and patterns. DAX (Data Analysis Expressions) formulas are leveraged for complex calculations, ensuring accurate insights.

Tools

Kaggle, Power BI(DAX), Microsoft Excel

Project #3

Humanitarian Insights-Dashboard

Data Collection

Source data from the Humanitarian team, encompassing records of violations and abuses across different provinces.

Problem Statement

Address the need for a comprehensive visualization tool to understand and analyze humanitarian violations for effective decision-making.

Methodology

Data Preparation and Cleaning:

• Thoroughly clean and structure the dataset to ensure accuracy and consistency.

Exploratory Data Analysis (EDA):

• Dive into the dataset to explore patterns, trends, and relationships among different types of violations.

Data Modeling:

• Utilize Power BI’s data modelling capabilities to create relationships and calculated measures for in-depth analysis.

  

Visualization Techniques:

• Line Graph:

  • Utilize a line graph to illustrate the trend of civilians killed over time, offering a temporal perspective on the gravity of the situation.

    

• Bar Chart:
  • Employ bar charts to showcase the magnitude of different types of abuses and violations, aiding in identifying the most prevalent issues.

• Heat Map:
  • Deploy a heat map to visualize the intensity of violations across provinces, highlighting areas of higher and lower occurrences.

• Shape Map:
  • Leverage a shape map to provide a geographic overview, offering insights into the spatial distribution of abuses.

• Pie Chart:
  • Implement a pie chart to categorize the types of abuses, providing a concise breakdown for easy interpretation.

Tools

Power BI (DAX, Power query), Power Automation, Microsoft Excel, SharePoint

Project #4

Social Media Insights - Dashboard

This Power BI dashboard provides a detailed analysis of social media performance, utilizing data collected from LinkedIn, Facebook, and Twitter.

Methodology

• Data Collection: Data collection is achieved using a combination of Power Query, M Query, and Power Automate:

• LinkedIn Data Collection: Utilizes the LinkedIn connector in Power BI along with Power Query for data transformation.

• Facebook Data Collection: Employs the Facebook Graph API via Power Query and M Query for extracting and shaping data.

• Twitter Data Collection: Leverages the Twitter API with Power Query and M Query for efficient data retrieval and transformation.

Problem Statement

The goal of this project is to provide a consolidated view of social media analytics to understand engagement, reach, and audience demographics. The dashboard aims to help users make informed decisions about content strategy and audience targeting.

Key Performance Indicators (KPIs)

The following key metrics are tracked on the dashboard:

• Engagement Metrics: Total likes, comments, shares, and engagement rate.

• Reach Metrics: Impressions, reach, and click-through rate (CTR).

• Audience Metrics: Demographics (age, gender, location), growth rate, and follower retention.

Tables, Filters, Bookmarks

• Tables: Utilize tables to present detailed data on post-performance, follower demographics, and more.

• Filters: Implement filters powered by M Query to allow users to customize the dashboard based on specific periods, social media platforms, or other relevant criteria.

• Bookmarks: Create bookmarks for saving specific views or settings using Power BI’s bookmarking feature.

  

Tools

The project utilizes the following tools:

• Power BI Desktop: The primary tool for designing and creating the dashboard.

• Power Query: Used for data collection and transformation, ensuring data is in the desired format.

• DAX (Data Analysis Expressions): Applied for creating custom calculations and metrics within Power BI.

• M Query: Used in conjunction with Power Query for advanced data manipulation and transformation.

• Power Automate: Integrated for automating data collection and refreshing processes, ensuring real-time insights.