CRISP-DM, SEMMA Methodologies for Data Mining | Big Data Analytics Tutorial | Lecture 2
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CRISP-DM, SEMMA Methodologies for Data Mining | Big Data Analytics Tutorial | Lecture 2
19 788 просмотров · 4 года назад
AmpCode
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19 788 просмотров · 4 года назад
This video is all about CRISP-DM, SEMMA Methodology for Data Mining which are the Traditional Data Mining Life Cycles that describes commonly used techniques that data mining experts use to solve problems in traditional BI data mining where we have discussed the different stages in both CRISP-DM, SEMMA Methodologies along with their brief history and main difference between them.
In the previous lecture we have seen, Introduction to Big Data where we can seen what is Big data, why to learn big data, what are the 3 Vs of Big Data what are the use cases (applications) of Big Data, benefits of big data analytics as well as challenges for processing and storing big data.
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Audience
This whole series has been prepared for it professionals aspiring to learn the basics of Big Data Analytics. Professionals as well as students who are into analytics in general may as well use this tutorial to gain good knowledge.
Prerequisites
Before you start proceeding with this tutorial, I am assuming that you have some kind of exposure to handling huge volumes of unprocessed data at an organizational level.
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