Ganga (http://cern.ch/ganga) is a job-management tool that offers a simple, efficient and consistent user experience in a variety of heterogeneous environments: from local clusters to global Grid systems. Experiment specific plugins allow Ganga to be customised for each experiment. This paper will describe these LHCb plugins of Ganga. For LHCb users, Ganga is the job submission tool of choice to the Grid as the LHCb specific plugins allow support for end-to-end analysis helping the user to perform his complete analysis with the help of Ganga. This starts with the support for data selection, where a user can select datasets from the LHCb Bookkeeping system. Followed by the setup for large analysis jobs with tailored plugins for the LHCb core software where jobs can be managed by the splitting of these analysis jobs with the subsequent merging of the result files. Furthermore, Ganga offers support for Toy Monte-Carlos to help the user tune their analysis. In addition, to describing the Ganga architecture, typical usage patters within LHCb and experience with the updated LHCb DIRAC 3 WMS will be shown.