A car company asked a data scientist to determine what type of customers are more likely to purchase their vehicles. However, the data comes from several sources and is in a relatively "raw format". What kind of processing can the data scientist perform on the data to prepare it for the Modeling stage?

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Business

Bo Hull

3 August, 07:37

A car company asked a data scientist to determine what type of customers are more likely to purchase their vehicles. However, the data comes from several sources and is in a relatively "raw format". What kind of processing can the data scientist perform on the data to prepare it for the Modeling stage?

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Samuel Riley · Answer 1

In order for data to be useful, it must be prepared so that it can be analyzed and processed. Preparing data usually takes several steps:

First the data scientist must edit the dа ta: correct incomplete, inconsistent or ambiguous answers. Then the data scientist must assign codes to possible answers so that they can be processed statistically. Then the data must be transcribed so that it can be processed. It is always a good idea to remove all inconsistencies and extreme values before starting to statistically process the data. Finally, the data scientist must decide which data analysis strategy should he/she use based on the previous steps and the characteristics of the dta itself.