Data Science

Describe and draw the CRISP data mining process

Business Understanding:
- Understanding the business problem and formulating a data science problem from it. (iteratively)
Data Understanding:
- Trying to understand the available data in context of the problem that is about to be solved.
Data Preparation:
- Deleting missing values, converting data into specific formats etc. to make them usable by specific technologies that lateron help to solve the problem (=prepare data for the tools it is going to be used with)
Modeling:
- Deriving some sort of pattern from the data
Evaluation:
- Assess the data mining results and validate model before deploying it. Also making sure that it helps to solve the overall business goal
Deployment:
- Using the model or parts of the model in a real environment
 
 

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