Data analytics and data science, though often used interchangeably, serve distinct roles in the realm of data-driven decision-making. Data analytics focuses on examining datasets to find trends and insights, primarily using historical data to inform business strategies. In contrast, data science encompasses a broader scope, including predictive modeling, machine learning, and statistical algorithms to extract meaningful patterns from large, unstructured data. While data analytics answers “what happened?”, data science explores “what will happen?” and “how can we make it happen?”. Understanding these differences is crucial for businesses aiming to leverage data effectively.
