The Model-Based Development (MBD) process has been the key enabler of technical advancement. MBD helps manage complexity, while making product development faster by bringing clarity and transparency to the entire product development process, specifically software components. Developing software using MBD has required extensive, sophisticated toolchains, like the ones provided by dSPACE, that allow for efficient rapid controls prototyping, automatic code generation, and advanced validation and verification techniques with hardware-in-the-loop (HIL) test systems. MBD is an efficient iterative process that allows engineers to improve quality and deliver on demanding needs of product variants in the current competitive environment.However, the MBD process described commonly using the ‘V-Cycle’ diagram leads to the generation of large volumes of data artifacts and work products. The iterative process, variants and versions of these artifacts lead to even larger amounts of data. To maintain efficiency while continuously improving the quality of products in the MBD paradigm, it is necessary to be able to manage this data in an efficient manner that is supportive of the development process.This paper discusses sources of data artifacts and work products that are created in the MBD process and critical requirements to enable reuse of this data. Further, we discuss criticality of integrating development tools and processes, such as test management, in a data management solution to increase process efficiency and effective management of data.