ARCHITECTURAL PATTERN FOR PERPETUAL INSIGHTS Use this architecture for systems that are making real-time decisions about new or existing entities. The perpetual insights pattern covers common use cases such as: Know Your Customer (KYC), Customer On-Boarding, Transaction Monitoring, Background Checks, Supply Chain Vetting, etc. Data Sources: A contributing data source will contain structured person or organization information. A data source will be a data store (e.g., SQL, NoSQL, NEO4J, MongoDB, HADOOP), a file (e.g., CSV), or a queue containing records. Loading historical data is handled by submitting all records in the data source to the transform function. After historical data has been loaded, adds, changes and deletes caused by ongoing business operations are to be submitted as tra

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