MAHA is in ongoing development. At present MAHA enables analysis of ebook browsing data. It can be used without modification on EBL book data. Additional adapters can be added to import data from other sources.
Analyses that MAHA can perform include:
MAHA is useful for understanding large-scale user behaviour across your whole ebook collection, down to an individual book. You can identify which parts of the collection see the most detailed reading, or that are frequently used for quick reference. For researchers, this enables multiple interrogations of the rich and complex patterns of real behaviour. Practitioners can interrogate their ebook collection data to validate acquisition strategies, or help form them. Whatever your interest in the behavior that occurs when users read electronic books, this tool provides insights that can help you find reliable answers, without costly manual analysis, or writing your own code. Unlike generic statistical packages, it understands from the ground up the specific measures and behaviours that apply in reading.
If you have particular patterns of analysis for ebook data that you would like to suggest, please email me with them. MAHA's front end is under active development, and MAHA should be released for public use in mid-2020.