Description
Your response should be 250-300 words for each discussion.
Discussion 1: Why are the original/raw data not readily usable by analytics tasks? What are the main data preprocessing steps? List and explain their importance in analytics.
Discussion 2 : What are the privacy issues with data mining? Do you think they are substantiated?
Explanation & Answer
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Running Head: DISCUSSION 1
1
Discussion 1: Data Preprocessing
Student’s Name
Professor
Course
Date
DATA PREPROCESSING
2
Data Preprocessing
Analytics tasks do no use raw data before it is preprocessed. Raw data is rogue. Rogue
data is dirty in the sense that it is not accurate, is incomplete, and lacks the proper consistency.
Some concerns that make raw data dirty include lack of proper organization. It also has outliers
that should be eliminated before using the data in making vital decisions. The data is also
voluminous and need to be reduced to a desirable and usable size. Sometimes the units or scales
that the data is presented with as raw are incomparable, and needs to be translated into common
units ...
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