The function of logistic regression analysis in data science is to model and predict binary outcomes based on one or more independent variables. This statistical method estimates the relationship between these variables and the probability of a particular event occurring, making it valuable for classification tasks. Logistic regression is widely used in various applications such as credit scoring, medical diagnosis, and marketing response prediction. Its interpretability and effectiveness in handling complex data make it a popular choice for data-driven decision-making.