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Description: Data science is integral in converting raw data into actionable insights for informed decision-making across domains. This survey explores the holistic data science processes, from collection to deriving insights. It introduces fundamental concepts, highlights ethical considerations in data collection, and covers data cleaning and preprocessing. The paper extensively explores Exploratory Data Analysis (EDA), emphasizing pattern discovery and anomaly detection. Model development and machine learning are central, emphasizing practical applications for extracting patterns. Detailed coverage of interpreting results and drawing insights demonstrates actionable information derivation. Case studies illustrate how insights inform decision-making. The survey addresses current data science challenges, speculating on future trends and advancements. A valuable resource for practitioners and researchers, it provides a comprehensive understanding of the journey from raw data to actionable insights in data science.