Your First Analysis
If you want to get started quickly, demo datasets are provided below in two sample CSV files. They represent customer demographic information and customer subscription information for a fake telecommunications company.
Go to Data → Datasets and upload a CSV file or connect a data source. Even a single spreadsheet is enough to get started. See Uploading Datasets.
Go to Data → Ontology and view where RootCause.ai has already created joins between different Entity, Time, or Location nodes. These are where different datasets are talking about the same thing.
If you see a missing join, or a join that shouldn't be there, you can click on it and make changes. For more advanced operations, like editing or adding individual concepts, see Ontology Concepts.
From the Ontology, you can create a combined Data View from multiple datasets for use in causal modeling and simulations. Simply click + New View" on the bottom-right, and then click on one of the joined nodes.
In the above example, you would press + New View and then Customer ID where a join exists between both datasets.
You're now ready to create a digital twin. If you want to perform operations or transformations on the data beforehand, you can find more details at Data Views.
Go to Digital Twin and select your data view.
Choose "Auto Discovery" to let RootCause.ai find causal relationships automatically. This typically takes a few minutes depending on your data size. See Creating a Digital Twin.
Once discovery is complete, run simulations to test interventions, find optimal actions, or explain outcomes. This is where insights turn into action. See Simulations.
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