Democratizing Data Science:Using Language Models for Intuitive Data Insights and Visualizations

The study explores the integration of the Phind-CodeLlama model into data science frameworks to facilitate intuitive and inclusive analysis of tabular data. By leveraging Phind-CodeLlama’s comprehensive knowledge base and custom-crafted prompts, the platform optimizes data management operations and significantly improves accessibility to data analysis tools. The research investigates the transformative potential of Phind-CodeLlama in improving data-driven decision-making processes by democratizing access to data insights. Through its user-friendly CSV data manipulation capabilities, the platform is designed to empower users from various backgrounds, especially those without a domain-specific background in data science, to conduct effective data analysis, formulate insightful questions, and create compelling visualizations. The study contributes to the advancement of user-friendly data analysis platforms, fostering a more democratized approach to data-driven decision-making.