Learning analytics brings together multiple systems, sources of data, stakeholders and processes. Modelling the various elements and how they should best fit together has been exercising the minds of a growing number of researchers and engineers. Inevitably, they do this in different ways according to their backgrounds and the systems to which they have been exposed or are developing. The uses of learning analytics vary considerably, as we have seen, and range from adaptive learning to course recommendation to early alert and student success and curriculum design. Each application requires a different configuration of data and tools, although they may draw on some of the same datasets.