Data analytics plays a crucial role in data science by enabling the extraction of meaningful insights from raw data. It involves using statistical techniques, algorithms, and tools to analyze data sets, identify patterns, and make informed predictions or decisions. In data science, analytics supports tasks such as data cleaning, transformation, visualization, and model building. It helps scientists and businesses understand trends, optimize processes, and drive strategic decision-making. By transforming data into actionable insights, data analytics is a key component of the data science workflow, bridging the gap between data collection and valuable outcomes.
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