Artificial intelligence life cycle

The artificial intelligence (AI) life cycle is a comprehensive framework comprising three main stages: data discovery, model development, and model deployment, collectively known as the "3Ds." Initially, data discovery involves identifying and obtaining relevant data, a phase that can consume up to 80% of a data scientist's time but is crucial for feature engineering. Next, the model development phase is where data scientists apply statistical and mathematical techniques to create analytical models that answer specific business questions, providing significant value. Finally, model deployment ensures that the outputs from these models are used by decision-makers, thus realizing the return on investment in AI. Tools like Starburst can streamline the data discovery phase by allowing data scientists to focus more on innovative model development, ultimately accelerating the AI project life cycle and enhancing organizational performance by enabling efficient data management across diverse sources.

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