Raw data is often dirty, misaligned, overly complex, and inaccurate and not readily usable by analytics tasks. Data preprocessing is a data mining technique which is used to transform the raw data in a useful and efficient format.
The main data preprocessing steps are:
•          Data consolidation
•          Data cleaning
•          Data transformation
•          Data reduction

1. Research each data preprocessing step and      briefly explain the objective for each data preprocessing step.  For      example, what occurs during data consolidation, data cleaning, data      transformation and data reduction?
2. Explain why data preprocessing is      essential to any successful data mining.  Please be sure to provide      support for your answer.

Raw data is often dirty, misaligned, overly complex, and inaccurate and not readily usable by analytics tasks. Data preprocessing is a data mining technique which is used to transform the raw data in a useful and efficient format.
The main data preprocessing steps are:
•          Data consolidation
•          Data cleaning
•          Data transformation
•          Data reduction

1. Research each data preprocessing step and      briefly explain the objective for each data preprocessing step.  For      example, what occurs during data consolidation, data cleaning, data      transformation and data reduction?
2. Explain why data preprocessing is      essential to any successful data mining.  Please be sure to provide      support for your answer.