A general scenario in Operational Modal Analysis (OMA) is that of performing measurements in several patches instead of performing all the measurements over the structure simultaneously. This scenario might arise due to various factors, such as availability of limited number of sensors, partial access to the structure etc. In these circumstances, the task is to patch together the data obtained from various patches so that modal parameters, representative of the entire structure, can be estimated. Two general approaches exist to accomplish this. First approach requires modal parameters to be estimated individually for each patch and then patching together the results. The other approach is to combine together the data from individual patches such that parameter estimation algorithms can be applied on the combined data resulting in global modal parameters directly. This paper studies the multi-patch OMA techniques and aims at providing useful insights and perspectives. The work presented in this paper lays down fundamental mathematical foundations of patching techniques in scenarios where data from different patches is first combined before applying parameter estimation algorithms. Further, a new Singular Value Decomposition (SVD) based approach is suggested in the paper for carrying out the patching procedure in the Pre-patching framework. The SVD based technique introduced in the paper also provides the basis of several other tools that help in evaluating overall effectiveness of the patching procedure, such as quality of acquired data, patch compatibility, validation of OMA assumptions regarding input excitation and time-invariance of the structure, etc. The concepts developed in this work are demonstrated by means of studies conducted on analytical and experimental systems.