The Software Platform comes with a business intelligence (BI) component that offers a visualization of simulations and multi-dimensional analysis. An easy to use, drag-and-drop interface gives users the capability to configure KPIs, create their own dashboards, and generate data exports. Users benefit from a range of data visualization alternatives such as pie, bar or line graphs, histograms, heat maps, geographical maps, scatter, and table charts.
Cosmo Tech’s simulation can be coupled with state of the art data science libraries including machine learning, scientific computing, optimization, and design of experiment, in particular by leveraging Spark computing libraries.
To create simulation-based experiments, users can develop their own Python analytics. Data scientists can leverage familiar frameworks like JupyterLab and PySpark libraries to implement algorithms such as uncertainty and sensitivity analysis, parameter optimization under constraints, and pre/post-processing analysis. Those algorithms use our simulation engine seamlessly through Spark.