Key tenets of agile and lean are to work collaboratively and to streamline your workflow respectively. In Figure 1 we see that data management is a collaborative effort that has interdependencies with other Disciplined Agile (DA) process blades and the solution delivery teams that data management is meant to support. This can be very different than the current traditional strategies. For example, with a DA approach, the data management team works collaboratively with the delivery teams, IT operations , and release management to evolve data sources. The delivery teams do the majority of the work to develop and evolve the data sources, with support and guidance coming from data management. The delivery teams follow guidance from release management to add the database changes into their automated deployment scripts, getting help from operations if needed to resolve any operational challenges. Evolution of data sources is a key aspect of Disciplined DevOps. This is very different than the typical traditional strategy that requires delivery teams to first document potential database updates, have the updates reviewed by data management, then do the work to implement the updates, then have this work reviewed and accepted, then work through your organization’s release management process to deploy into production.