The  Data  Analytics  Lifecycle  is  designed  specifically  for  Big  Data  problems  and  data science  projects.  The  lifecycle  has  six  phases,  and  project  work  can  occur  in  several phases at once. For most phases in the lifecycle, the movement can be either forward or backward. This iterative depiction of the lifecycle is intended to more closely portray a real  project,  in  which  aspects  of  the  project  move  forward  and  may  return  to  earlier stages  as  new  information  is  uncovered  and  team  members  learn  more  about  various stages of the project. This enables participants to move iteratively through the process and drive toward operationalizing the project work