The SAX (Symbolic Aggregate approXimation) function transforms a time series data item into a smaller sequence of symbols that can then be analyzed using Teradata Introduction to nPath or Shapelet Functions (ML Engine), or by other hashing or regular-expression pattern matching algorithms.
The SAX algorithm was developed by Eamonn Keogh and Jessica Lin in 2002. For information about the SAX algorithm, see: