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Unlocking the Power of ATOM AVA: A Comprehensive Guide to Key Use Cases
This blog explains the Anuta ATOM AVA (AI-Powered Virtual Assistant) use cases in detail thus helping you simplify network management and automation.
Learn how Anuta Networks instills Service & Operational agility into your networks with Anuta ATOM & ATOM Cloud – Your Next-generation Network Automation & Assurance Solutions
Learn how Anuta Networks instills Service & Operational agility into your networks with Anuta ATOM & ATOM Cloud – Your Next-generation Network Automation & Assurance Solutions
Learn how Anuta Networks instills Service & Operational agility into your networks with Anuta ATOM & ATOM Cloud – Your Next-generation Network Automation & Assurance Solutions
Learn how Anuta Networks instills Service & Operational agility into your networks with Anuta ATOM & ATOM Cloud – Your Next-generation Network Automation & Assurance Solutions
Behind the scenes of any business process management workflow is a series of intricate decision-making steps that operate behind the scenes. A mechanism is employed to cross-check input data against specific criteria before accurately routing the data to reach the appropriate conclusion.
Whether it’s the seasonal recommendation of holiday movies on your social media feed or the sudden price surge for flights to popular holiday destinations, a Decision Model and Notation (DMN) model provides a comprehensive structure for making business decisions. This model presents decision logic through diagrams and tables, enabling end-to-end clarity.
To implement this model, ATOM establishes the N number of tables in the input session, along with the N number of key-value pairs in the output session. Subsequently, we can pass the variable name to DMN, which will conduct a search in the input session and retrieve the relevant output table variables in a JSON format based on the corresponding table name match.
The DMN offers a significant breakthrough in identifying test cases, reducing the total cost and time of testing efforts through the graphical decomposition of requirements.
DMN increases business transparency by helping all stakeholders understand a complex decision-making domain using easily readable diagrams.
The notations for decisions are augmented in the form of Decision Tables that provides flexibility to express logic in different scenarios using the same table.
A standard framework for decision models provides a structured context for developing and managing predictive analytic models enabling the development of a library of reusable decision-making components.
The development of decision systems using specifications that may be automatically validated and executed allows business rules to be defined simply and reliably in unambiguous decision tables.
ATOM also eliminates the exhaustive process of providing different inputs based on conditional matching by creating the DMN tables with the required variables
ATOM facilitates easy integration of the DMN tables into the workflows without requiring extra plugins and GUI.
Through DMN, ATOM provides a structured context for different workflow inputs, reducing the complexity and creating a straight-through process.
When a user provides input in workflow execution, a DMN block is created inside it that can be accessed later to fetch the respective output variables based on the input provided without repeating the process.
ATOM
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