In today's data-driven world, organizations are constantly seeking ways to leverage data for gaining insights, making informed decisions, and driving business growth. This is where data science comes into play. Data science is a multidisciplinary field that combines statistical analysis, machine learning, and domain expertise to extract valuable knowledge and insights from data. To achieve success in data science projects, it is crucial to follow a systematic approach known as the data science life cycle. In this article, we will provide a detailed explanation of the data science life cycle, its various stages, and how it contributes to successful data-driven initiatives. Problem Identification The initial phase of the data science life cycle encompasses the precise delineation of the problem statement and project objectives. This stage is of paramount importance as it lays the cornerstone for the entire process. Collaborating with stakeholders and domain experts is imperative to c...