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
The main data preprocessing steps are:
• Data consolidation
• Data cleaning
• Data transformation
• Data reduction
- 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?
- Explain why data preprocessing is essential to any successful data mining. Please be sure to provide support for your answer.
