Modeling temporal consistency in data warehouses

Real-world changes are generally discovered delayed by computer systems. The typical update patterns for traditional data warehouses on an overnight or even weekly basis enlarge this propagation delay until the information is available to knowledge workers. The main contribution of the paper is the identification of two different temporal characterizations of the information appearing in a data warehouse: one is the classical description of the time instant when a given fact occurred, the other represents the instant when the information has been entered into the system. We present an approach for modeling conceptual time consistency problems and introduce a data model that deals with timely delays and supports knowledge workers to determine what the situation was in the past, knowing only the information available at a given instant of time.