In the era of big data and machine learning, businesses need to employ a structured methodology to make sense of the data and extract insights that can drive business decisions. One methodology that has gained immense popularity over the past few years is CRISP-DM. CRISP-DM stands for Cross-Industry Standard Process for Data Mining and is a widely used methodology for data mining and machine learning projects.
The Cross Industry Standard Process for Data Mining (CRISP-DM) is a process model that outlines the key steps involved in a data mining or machine learning project. It is an iterative process that involves six phases: Business Understanding, Data Understanding, Data Preparation, Modeling, Evaluation, and Deployment. Each phase is distinct, with its own set of tasks, and the results of one phase feed into the next.
The CRISP-DM methodology includes the following phases:
Data analytics offers numerous benefits to businesses, including:
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