One of the weakest points of scientific research is the loss of data. A tiny fraction of the information generated onsite is published or released to public knowledge, and many useful studies end up stored in papers or emails without being utilized. Live ANDES is a mobile-cloud shared workspace designed to address this problem, promoting citizen science, data collection and analysis for wildlife conservation. It works by gathering geo-localized data provided by the scientific community, amateur naturalists, park rangers and people at large through web and mobile applications. Live ANDES offers filters, visualization and download options to work with existing data. Researchers can use this new information to identify species, ranges of distribution, and detect key habitat factors and potential threats to their conservation. Live ANDES is implemented using the Backend as a Service pattern on Microsoft Azure to manage the processing of the large amounts of data generated from sightings. It includes an API for mobile and desktop clients hosted in an Azure Virtual Machine, cloud storage and connection with external services to complement the existing information about recorded sightings. This paper discusses Live ANDES software design, architecture and a study case, in order to demonstrate an actual application of data management in the cloud and its impact on conservation.