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Data Preprocessing Data Quality and Major Tasks in Data Preprocessing Data Cleaning Data Integration Data Transformation and Data Discretization Data Reductionist Mining1 Data Quality and Major Tasks
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Gather the raw data from various sources
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Clean the data by removing duplicates, filling in missing values, and correcting errors
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Normalize the data by scaling or standardizing the features
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Handle categorical variables by encoding them into numerical values
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Split the data into training and testing datasets
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What is data preprocessing in data?
Data preprocessing is the process of cleaning and preparing raw data for analysis.
Who is required to file data preprocessing in data?
Data analysts, data scientists, or anyone working with data is required to file data preprocessing.
How to fill out data preprocessing in data?
Data preprocessing can be filled out using software tools such as Python, R, or tools provided by data processing platforms.
What is the purpose of data preprocessing in data?
The purpose of data preprocessing is to ensure data quality, remove inconsistencies, and prepare the data for analysis.
What information must be reported on data preprocessing in data?
Information such as data cleaning steps, data transformations, and any preprocessing techniques applied must be reported on data preprocessing.
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