A time series analysis in data science involves studying datasets that are indexed in time order to identify trends, patterns, and seasonal variations. This analytical technique enables analysts to forecast future values based on historical data by employing models like ARIMA (AutoRegressive Integrated Moving Average) or exponential smoothing. Time series analysis is critical in various domains such as finance for predicting stock prices, economics for analyzing economic indicators, and even in environmental sciences for monitoring climate changes. It enhances decision-making by providing insightful forecasts.