The data science life cycle

Data science has emerged as a critical discipline, enabling organizations to derive valuable insights from their data and drive better decision-making. At the heart of data science lies the data science life cycle, a systematic, iterative process that guides data-driven problem-solving across various industries and domains. This life cycle outlines a series of steps that data scientists follow to ensure they address the right problem and deliver actionable insights that create real-world impact.

The first stage of the data science life cycle involves defining the problem, which entails understanding the business context, articulating objectives, and formulating hypotheses. This crucial stage establishes the entire project’s foundation by establishing a clear direction and scope. Subsequent stages in the life cycle focus on data collection, preparation, and exploration, collectively involving gathering relevant data, cleaning and preprocessing it...