The Data Analytics Lifecycle is a structured approach to solving data-driven problems and generating insights. It consists of six key phases: Discovery, where business objectives are identified; Data Preparation, involving data collection and cleaning; Model Planning, to choose analytical techniques; Model Building, where models are developed and tested; Communicate Results, focusing on presenting findings; and Operationalize, where solutions are deployed for real-world use. This lifecycle ensures a systematic workflow that aligns data efforts with business goals, leading to informed decision-making.