Conversational Interfaces For Dataops And Pipeline Monitoring: Democratizing Data Infrastructure Management Through Natural Language Processing

Abstract

Putting conversational interfaces into DataOps platforms makes it much simpler to get to complex data management systems. This paradigm breaks down the obstacles that have prevented non-technical people from keeping an eye on how pipelines are working, spotting system issues, and getting helpful information from data setups. By using AI agents and processing natural language, businesses can change common language into technical actions. The system has AI agents for talking with users, an API for connecting to the platform, and creating responses for easy-to-understand communication. Setting this up means working closely with DataOps platforms like Apache Airflow and Databricks Jobs. This calls for careful data coordination and API methods. Examples show better operations, more people involved, and quicker problem-solving in areas like finance and healthcare.