at the time of the creation of the row. Temporal snapshots By applying temporal database theory and modeling techniques the temporal snapshot fact table allows to have the equivalent of daily snapshots without really having daily snapshots. It introduces the concept of time Intervals into a fact table, allowing saving a lot of space, optimizing performances while allowing the end user to have the logical equivalent of the "picture of the moment" they are interested in. Steps in designing a fact table Identify a business process for analysis (e.g., sales). Identify measures of facts (sales dollar), by asking questions like 'what number of X are relevant for the business process?', replacing the X with various options that make sense within the context of the business. Identify dimensions for facts (product dimension, location dimension, time dimension, organization dimension), by asking questions that make sense within the context of the business, like 'analyze by X', where X is replaced with the subject to test. List the columns that describe each dimension (region name, branch name, business unit name). Determine the lowest level (granularity) of summary in a fact table (e.g. sales dollars). An alternative approach is the four-step design process described in Kimball: select the business process, declare the grain, identify the dimensions, and identify the facts. References Data warehousing