Modeling dataflows 🚀
Modeling dataflows improves efficiency, security, and control over their processes.
Naming and structuring a dataflow makes it easier to manage and monitor. The use of notifications ensures rapid response to errors, minimizing disruption and operational risk. Assigning attributes organizes workflows more effectively, and aligns tasks with business goals. Configuring cutoff points helps control dataflow behavior and prevents issues. In addition, dataflow modeling improves searchability and user management by enabling selective access and enhancing security, governance, and compliance. Overall, it results in more efficient, reliable, and well-governed business operations.
Main features of dataflow models
Modeling a dataflow enriches it with specific information in a way that makes it more meaningful to business users.
Modeling features include:
labeling of specific business flows so that they are recognized for a function
management of the arrival of files
processing of files on specific nodes through cut-offs
definition of dataflow matching rules
Existing dataflow models are listed on the Dataflow Models page, which can be reached by clicking the option on the toolbar to the left. When Data Watcher is in a bundle with Data Mover, Existing dataflow models are listed in Design → Dataflow Models.
Dataflow models can be created from a flow already in Data Watcher or from scratch. Read the following pages for details.
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