Analyze various data pre-processing techniques such as data cleaning, data integration, data transformation, and data reduction. Explain the significance of each technique in improving the quality of data for mining and provide examples of scenarios where each technique would be applied.

Data warehousing and data mining involve collecting, storing, and analyzing vast amounts of data to derive valuable insights. Before effective data mining can occur, data must undergo a series of pre-processing techniques to ensure its quality and usability. These techniques include data cleaning, data integration, data transformation, and data reduction. Each plays a crucial role in enhancing the data quality and making it suitable for mining.

1. Data Cleaning:
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