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In data science pipelining, EDA is one of major step when considering data analysis tools. Storytelling is currently becoming a frequent practice in the data visualization field due to the need of data stories that can be expressed in vivid modern visualization genres. Voice interaction is important because it enables quicker, hands-free exploration of data, reducing reliance on manual inputs and improving accessibility. The majority of the current systems prioritize on textual representation or visual illustration of the outcome. This Proposed work is different in manner as this EDA tool is the integration of 1. Verbal input (Asking voice queries) 2. Visual creations (charts and scattered plots) 3. Vocal (spoken Output) forming a coordinated multimodal communication application between human and data science. It lets users to explore data visually, read explanatory narratives, and listen to spoken output. This approach is not found in previous EDA or voice interface studies, also existing studies have some interfaces that can frequently expect some level of coding proficiency, making the application inconvenient for non-programmers, scholars, and users with visual weaknesses. By transforming complex data analysis into a lively, meaningful storytelling experience. The interactive model optimizes user engagement and availability with changing technical and cognitive abilities.