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A data scientist has crafted a feature engineering notebook that leverages the pandas library. As the volume of data processed by the notebook grows, the runtime significantly escalates and the processing speed decreases proportionally with the size of the included data. What tool can the data scientist adopt to minimize the time spent refactoring their notebook to scale with big data?