A major pre-award administrative challenge research universities face is turnaround time for generation of high-quality NIH Data Training Tables for NIH training grants (e.g., T32, K12, TL1, KL2, R25s) which are required for training grant submission proposals to the National Institutes of Health (NIH). Universities with dedicated training grant submission offices generally require data preparation following a structured timeline of several months in advance of the grant submission due date, while other universities with less or no dedicated support for training grant submissions use an ad hoc approach. In these cases, department or program administrators may collect the data manually, in Excel or REDCap, or similar manually maintained methods for those tables requested by the specific NIH grant announcement for the relevant participating graduate predoctoral and/or postdoctoral (including clinical) training programs across the university, depending on the training focus and the "participating faculty" provided by the proposed program director (PD/PI) for the grant. We describe an efficient "federated" method of data collection and construction for NIH Tables (2, 4, 5A/B, 6A/B & -8A part III/8C part III) for new and renewal applications by combining the use of REDCap and NIH xTRACT, leveraging the strengths of each.