SCANDAL MURTY
Aspiring Data Analyst | Operational & Logistical Mindset
A detail-oriented professional with seven years of operational logistics experience, pursuing a transition into data analysis. Demonstrates a consistent record of achieving full compliance and applies foundational expertise in SQL, Python, and Tableau to address complex business challenges.
Technical & Analytical Skills
Featured Data Case Study: Top 2,000 Highest Rated TV Shows
1. Data Exploration & Navigation
Goal: Navigate and audit a large-scale entertainment dataset.
Initial exploration of a comprehensive dataset containing Top 2,000 Highest Rated TV Shows. Focused on assessing data quality and preparing the structure for multi-tool analysis.
View Sample Dataset on GitHub
View Original Data File From Kaggle
2. Targeted Extraction with SQL
Goal: Filter "Action & Adventure" leaders using relational operators.
Utilized SQL queries to isolate the top 10 performing shows within the "Action and Adventure" category. Applied ORDER BY and LIMIT functions to rank shows by user rating, ensuring precise extraction that mirrors the precision required in my previous technical support roles.
3. Python Scripting for Niche Analysis
Goal: Automate "Horror" genre extraction using the Pandas library.
Leveraged Python to programmatically identify the top 10 Horror shows. By utilizing Pandas DataFrames to filter for genre-specific strings, I demonstrated how automation can reduce the manual tracking time often found in traditional inventory management systems[cite: 18].
4. Tableau Insight Visualization
Goal: Visualize popularity distributions across all categories.
Translated raw data into a Tableau interactive graph to compare genre popularity. This visual summary provides stakeholders with "at-a-glance" insights into market demand, similar to reporting critical stock levels to management.