Time-oriented data models

Time-oriented data models organize information with a focus on its changes over time. They track not only the current state of data but also historical and future states, capturing when data was created, modified, or relevant. This approach is essential for applications like tracking customer interactions, stock prices, or medical records, where understanding the timing and sequence of events provides valuable insights. By incorporating timestamps or periods, these models enable accurate analysis of how data evolves, supporting better decision-making and historical analysis.