Research Data Management is the care and maintenance of the data that is produced during the course of a research cycle. It is an integral part of the research process and helps to ensure that your data is properly organized, described, preserved, and shared.
Funding agencies (especially the federal government) are increasingly requiring data to be made publicly available and requiring the creation and execution of a Data Management Plan (DMP), which is a formal document that states what you will do with the data during and after your research project.
Whether you are an undergraduate, graduate, or faculty member working on a research project, managing your data well is one of the best ways ensure standardization, reproducibility, and the ability to disseminate your research to other interested parties as well as save you time in the long run.
There are sites, such as the Open Science Framework, that can help you manage your project through its research life cycle as well.
Source: https://blogs.ntu.edu.sg/lib-datamanagement/data-lifecycle/
This pictorial representation of Research Data Management indicates the best practice when it comes to managing your data. It begins at the top with Data Creation and moves clockwise through the process. After data is created, it is then processed and analyzed. Data should then be preserved into archival formats and made accessible to the public.This will enable reuse by other researchers who will then create their own data and the cycle will begin again. Though this cycle assumes that each stage will take place in its entirety before moving onto the next stage, practice dictates that there may be several iterations of creation, processing, and analysis before it is ready to be preserved.