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Data Professional Survey Dashboard

Project Description

Developed entirely in Power BI, this project encompasses both DATA CLEANING and VISUALISATION tasks, providing a seamless and comprehensive analysis experience.

The dashboard features seven interactive visualizations designed to provide actionable insights into the survey data:

  • Average Salary By Job Title: Analyzes salary distribution across different job titles within the data professional community.

  • Country of Survey Taker: Enables users to filter data based on the country of survey respondents, offering geographic insights.

  • Favorite Programming Language: Illustrates the popularity of various programming languages among data professionals.

  • Average Salary by Male/Female: Compares the average salary between male and female survey respondents, highlighting potential gender-based salary discrepancies.

  • Happy with Work Life Balance: Utilizes a gauge visualization to indicate the level of satisfaction with work-life balance among survey participants.

  • Happy with Salary: Presents survey respondents' satisfaction levels with their salaries through another gauge visualization.

  • Survey Takers: Provides a card visualization displaying the count of survey participants, offering a quick overview of the survey sample size.

  • Average Age of Survey Takers: Displays the average age of survey respondents, offering demographic insights into the data professional community.

 

Data Cleaning Steps:

  1. Transformed raw data through Power BI's data transformation capabilities.

  2. Streamlined the dataset by removing unnecessary columns to focus on relevant insights.

  3. Utilized the Split Column feature to clean and extract meaningful information from four columns.

  4. Introduced a custom column to calculate the average salary, enhancing the dataset with valuable aggregated information.

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Visualisation Development Highlights :

  1. Created Stacked Bar Chart Visualisation for Average Salary By Job Title

  2. Created Treemap Visualisation for Country of Survey Taker

  3. Created Stacked Coloumn Chart Visualisation for Favourite Programming Language

  4. Created Pie Chart Visualisation for Average Salary by Male/Female

  5. Created Gauge Visualisation for showing Happy with Work Life Balance

  6. Created Gauge Visualisation for showing Happy with Salary

  7. Created Card Visualisation for Count of Survey Takers and Age of Survey Takers
     

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