This means results may be be verified and reproduced by anyone with access to the notebook. Notebooks are project packages which contain all the components and dependencies of an analysis, including code, data, comments and other technical documentation, charts and deployment capabilities. Build Confidence with Reproducible Results.Since notebooks are saved and searchable, rather than spending time "recreating the wheel", RCloud Data Scientists may reuse notebooks or parts of notebooks for similar projects. In this environment, data scientist teams benefit from easier sharing of scripts and data feeds, experiments, annotations and automated recommendations which are well beyond what traditional individual or locally based development environments provide. RCloud employs notebooks composed of cells where topics may easily be broken up into concepts and where the relationship between the concepts can be easily understood.
RCloud enables Data Scientists to find value in data by sharing ideas and techniques with each other and results with any user in the community. Increase Insights on Big Data Analyses through Collaboration.
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