Research Data Management (RDM) might sound complicated, but it is simply the effective stewardship of data that you create in the course of conducting your research. In fact, if you have conducted research in the past, you have probably already done research data management! Tasks including organizing and naming your files, tracking different versions of your work, and considering who should have access to your data are all part of the research data management cycle. RDM in the context of this site refers to systematically approaching these tasks so that you don't miss anything, and so that you are taking advance of the resources available to assistant with managing your research data.
The RDM process will look somewhat different depending on the type of data collected during the course of your research. Some data (such as data from experiments) is reproducible, while other types of data (like field notes) may not be. Some data is confidential, while other data does not have these restrictions. Data is often used to provide evidence for publications, but it can also be used for other purposes, including verification of findings, and reuse for other purposes. Regardless of these variations, the basic research data life cycle is similar:
Image from Jisc
As you can see, the research data lifecycle begins when you are planning your project (before you even collect any data) and continues throughout your collection and use of the data, and on to long-term security, storage, and potentially re-use of the data.