Ghulam Murtaza Portfolio

📊 Dynamic Charting: Developed a system for users to easily toggle between different chart types, enhancing interactivity.

🌍 Geographic Analysis: Visualized customer complaints on a map, breaking them down by state to highlight areas with high feedback.

📉 Trends Over Time: Utilized a line chart to showcase how complaint resolutions have changed over time, offering a historical perspective.

🖱 User Interaction: Incorporated dynamic filters, allowing users to tailor the data they view, enhancing user experience.

🚀 Expansion Ideas: Outlined potential improvements, including introducing date-specific filters and presenting data in more varied chart formats.

📊 Data Integration: Imported four tables of COVID-19 data (cases, deaths, death percentages, locations) from SQL Server to Tableau Public for unified visualization.

📝 Global Overview: Developed a text chart detailing total cases, fatalities, and death rates across different locations, providing a snapshot of global pandemic impact.

🌍 Continental Analysis: Visualized total deaths using a bar chart, facilitating a comparative study of the pandemic's toll on different continents.

🗺 Interactive Geographical Insights: Constructed a dynamic world map charting infection rates country-by-country, enabling granular exploration of global spread patterns.

📈 Time Series Evaluation: Illustrated the virus's propagation with a line graph, tracing infection trends over time in selected countries, augmented with potential forecast data.

📈 Monthly Breakdown: Displayed a detailed monthly breakdown that showcases both sales and returns with a dynamic filter mechanism, allowing users to focus on either 'sales' or 'returns'.

🔝 Peak Products: Capitalizing on the high sales months of October and November, the dashboard visualizes the top 5 products that secured the most sales during this period.

🌍 Geographical Sales Distribution: An illustrative chart detailing sales distribution across various countries, providing insights into the global reach and performance of the products.

⏰ Peak Sales Hours: A comprehensive pie chart presenting the hours during which sales peak, assisting businesses in optimizing their operational hours for maximum sales.

📆 Daily Sales Analysis: A day-wise breakdown of sales, allowing stakeholders to assess daily performance and identify trends or patterns in consumer purchasing behaviors.

📊 Data Integration: Integrated survey data into Power BI. Split, renamed, and cleaned columns for a smoother analysis process.

📉 Visual Breakdown: Visualized key insights such as average age (~30 years), data scientists' average salary ($93K), and the dominance of Python among programming languages.

🌍 Global Perspective: Delineated respondent demographics, underscoring US, India, and Canada as primary contributors. Highlighted salary disparities: US data scientists at $139K vs. India's at $68K.

🙂 Job Satisfaction: Assessed work-life balance (5.74/10) and salary contentment (4.36/10), providing a holistic view of respondent sentiment.

🚻 Gender Pay Insights: Illustrated the subtle pay disparity with females averaging $55K and males $53K.