Time Series, Dense Representations, and Sparse Representations of Temporal Data - Analytics Database - Teradata Vantage

A time series is an ordered sequence of measurements of a variable that are arranged according to the time of occurrence. Time series are typically measured at some constant frequency and the data points are generally, but not necessarily, spaced at uniform time intervals.

The EXPAND ON clause enables various forms of time series expansion on a PERIOD column value of an input row by producing a set of value-equivalent rows, one for each granule in the specified time period. The number of granules is defined by the anchor name you specify for the clause.

You can expand sparse PERIOD representations of relational data into a dense representation of the same data. Data converted to a dense form can be more easily manipulated by complex analyses such as moving average calculations without having to write complex SQL requests to respond to business questions made against sparse relational data.