This presentation describes the Bayesian Block algorithm in the context of its application to analysis of time series data from the Fermi Gamma Ray Space Telescope. More generally this algorithm performs optimal segmentation analysis on sequential data in any mode, with arbitrary sampling and in the presence of gaps and exposure variations. A new procedure for correcting for backgrounds is also described.