Wearable accelerometers provide detailed, objective, and continuous measurementsof physical activity (PA). Recent advances in technology and the decreasing cost ofwearable devices led to an explosion in the popularity of wearable technology inhealth research. An ever-increasing number of studies collect high-throughput, sub-second level raw acceleration data. In this paper, we discuss problems related to thecollection and analysis of raw accelerometry data and refer to published solutions. Inparticular, we describe the size and complexity of the data, the within- and between-subject variability, and the effects of sensor location on the body. We also discusschallenges related to sampling frequency, device calibration, data labeling, and multi-ple PA monitors synchronization. We illustrate these points using the DevelopmentalEpidemiological Cohort Study (DECOS), which collected raw accelerometry data onindividuals both in a controlled and the free-living environment.