Temporal Data Analysis

Temporal Data Analysis involves examining data that changes over time to identify patterns, trends, or behaviors. It looks at how information evolves, such as sales figures over months, temperature changes through seasons, or social media activity over days. By analyzing this time-related data, we can make better predictions, understand historical contexts, and inform decision-making. For example, businesses might use it to recognize peak sales seasons, while researchers could track disease outbreaks to understand their spread. In essence, it's about extracting meaningful insights from data that is inherently linked to time.