Data Professional Survey Dashboard
Survey Dashboard Overview
The Survey Dashboard provides a deep dive into the experiences and satisfaction levels of data professionals across various dimensions. This project highlights my ability to manage, analyse, and visualize survey data, transforming it into meaningful insights that can drive strategic decisions.
Key Objectives
The dashboard aims to achieve the following:
Job Satisfaction Analysis: Understand how satisfied data professionals are with various aspects of their current positions, such as management, work-life balance, and compensation.
Career Challenges: Explore the difficulties professionals face when entering the data field and the factors most important to them when considering a new job.
Demographic Insights: Analyse how demographic factors such as age, gender, and location influence career satisfaction and challenges.
Features and Functionality
This dashboard is designed with the following features to maximize its usability:
Interactive Visualizations: The dashboard includes dynamic charts and graphs that allow users to explore survey responses in detail, broken down by different demographic segments.
Filtering Capabilities: Users can filter data by key variables such as age, gender, and education level, enabling customized analysis and insights.
User-Friendly Interface: The dashboard is intuitive and easy to navigate, ensuring that all users, regardless of technical proficiency, can extract valuable insights.
Target Audience
This dashboard is intended for HR professionals, data industry leaders, and market researchers who seek to understand the trends and challenges within the data profession. The insights derived from this dashboard can inform recruitment strategies, employee retention efforts, and overall industry trends.
Technical Implementation
The Survey Dashboard was developed using advanced data processing and visualization tools:
Power BI: Used to create the interactive visualizations and overall dashboard layout.
Excel: Served as the primary data source, where raw survey data was stored and processed.
Power Query: Employed to clean and transform the data, ensuring it was ready for analysis in Power BI.
DAX (Data Analysis Expressions): Utilized within Power BI to perform complex calculations, such as aggregating satisfaction scores and filtering data dynamically.
Insights and Impact
The dashboard reveals several key insights:
Satisfaction Levels: Management and work-life balance are crucial factors in overall job satisfaction, with variations observed across different age groups and genders.
Career Entry Challenges: Many professionals find it "Very Difficult" to break into the data field, highlighting a need for better training and entry-level opportunities.
Job Search Priorities: When considering a new job, remote work and better salary are the most significant factors, indicating shifting priorities in the post-pandemic workplace.
These insights provide valuable guidance for organizations looking to attract and retain top talent in the data profession, helping them align their offerings with the needs and desires of current and prospective employees.
The csv file can be found on my GitHub Repo