The data science lifecycle is a systematic framework guiding projects from problem definition to deployment. It structures processes like data collection, cleaning, analysis, and modeling to deliver actionable insights. Businesses, analysts, and engineers use it to solve complex problems, optimize decisions, and drive innovation. Ultimately, stakeholders, including executives and product teams, benefit from data-driven strategies that improve efficiency and outcomes.
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