![]() ![]() In case, the use or relevance of some piece of data is unclear to the development team, they can momentarily step back, to understand the business and how it benefits from that piece of information. #Crisp meaning how toIn this step, team members brainstorm on how to extract the best value of the pieces of information. ![]() This is a crucial part of the project because it defines how viable and trustworthy can be the final results. It checks the quality of the data, in several terms, such as data completeness, values distributions, data governance compliance. The second step is Data Understanding and its objective is to know what can be expected and achieved from the data. For example, develop team should know by now that the objective is to increase sales, and after the step is over, understand what is the client selling and how they sell it. The goals of the project should be defined before the project starts. The product of this step is that the development team understands the context of the project. It is composed of meetings, online meetings, documentation reading, specific field learning, and a long list of ways they help the development team, make questions about relevant context. The first step is Business Understanding and its objective is to give context to the goals and to the data so that the developer/engineer gets a notion of the relevance of data in that particular business model. Those steps are Business Understanding, Data Understanding, Data Preparation, Modeling, Evaluation, and Deployment. It consists of 6 steps to conceive a Data Mining project and they can have cycle iterations according to developers’ needs. Kenneth Jensens image describing the stepsĬRISP-DM stands for Cross Industry Standard Process for Data Mining and is a 1996 methodology created to shape Data Mining projects. ![]()
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