Understanding the nature and characteristics of E-business workloads is a crucial step to improve the quality of service offered to customers in electronic business environments. Using a multi-layer hierarchical model, this paper presents a detailed multiscale characterization of the workload of two actual E-business sites: an online bookstore and an electronic auction site. Our analysis of the workloads showed that the session length, measured in number of requests to execute E-business functions, is heavy-tailed, especially for sites subject to requests generated by robots. An overwhelming majority of the sessions consists of only a handful requests. This seems to suggest that most customers are human (as opposed to robots). A significant fraction of the functions requested by customers were found to be product selection functions as opposed to product ordering. An analysis of the popularity of search terms revealed that it follows a Zipf distribution. However, Zipf's law as applied to E-business is time scale dependent due to the shift in popularity of search terms. We also found that requests to execute frequent E-business functions exhibit a similar pattern of behavior as observed for the total number of HTTP requests. Finally, our analysis demonstrated that there is a strong correlation in the arrival process at the HTTP request level. These correlations are particularly stronger at intermediate time scales of a few minutes.