Discussion (Chapter 3) Why are the originalraw data not readily us.docx
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Original or raw data is often not directly suitable for analytics due to issues like noise, irregularities, and missing values that can lead to misleading insights. The main data preprocessing steps include data cleaning, transformation, integration, and reduction, each critical to ensuring that the data used in analytics is accurate and relevant. These steps enhance the data's quality, making it more manageable for analytical processes and ultimately leading to better decision-making results (Author, Year).
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Discussion (Chapter 3) Why are the originalraw data not readily us.docx
- 1. Discussion (Chapter 3): 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. Note: Response should be 250-300 words. There must be at least one APA formatted reference (and APA in-text citation) to support the thoughts in the post. Do not use direct quotes, rather rephrase the author's words and continue to use in-text citations