![]() ![]() This step focuses on understanding the objectives of the project and requirements from the perspective of the business. Steps in CRISP-DM Understanding the problem statement Let’s devise a solution to predict the next days’ electricity consumption. Now that we have understood what’s the business problem. To understand CRISP-DM methodology, let’s look at a simple case study.Ī utility company wants to predict the next days’ demand for electricity, to allocate necessary resources for power generation. ![]() A significant increase in the usage of this methodology can be seen after conducting a poll in 20, as shown in the below image:Īccording to Wikipedia, “Data mining is a process model that describes commonly used approaches that data mining experts use to tackle problems… it was the leading methodology used by industry data miners.” What is CRISP-DM?Īccording to this article, CRISP-DM stands for CRoss-Industry Standard Process for Data Mining and was developed in 1996.ĬRISP-DM is one of the most preferred techniques used to build data mining projects. With the increase in the projects’ complexity, it is recommended to follow a standard framework to achieve goals faster.
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