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What is Data Cleaning

Chapter 189
Encyclopedia of Information Science and Technology, Third Edition
Process of detection and correction of incomplete, corrupted or inaccurate data from a data source.
Published in Chapter:
Record Linkage in Data Warehousing
Alfredo Cuzzocrea (ICAR-CNR and University of Calabria, Italy) and Laura Puglisi (GESP Geographic Information Systems, Italy)
Copyright: © 2015 |Pages: 10
DOI: 10.4018/978-1-4666-5888-2.ch189
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Chapter 9
Using Data Mining Techniques to Predict Obstetric Fistula in Tanzania: A Case of CCBRT
Is the process of detecting and correcting the corrupt or inaccurate records from a record set, table, or database and refers to identifying incomplete, incorrect, inaccurate or irrelevant parts of the data and then replacing, modifying, or deleting the dirty data.
Published in Chapter: Using Data Mining Techniques to Predict Obstetric Fistula in Tanzania: A Case of CCBRT; From: Handbook of Research on Nurturing Industrial Economy for Africa’s Development
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Chapter 11
Restaurant Sales Prediction Using Machine Learning
The process of identifying and removing or correcting errors, inconsistencies, and inaccuracies in a dataset in order to improve its quality and usefulness for analysis.
Published in Chapter: Restaurant Sales Prediction Using Machine Learning; From: Handbook of Research on AI and Machine Learning Applications in Customer Support and Analytics
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Chapter 6
Big Data Preprocessing, Techniques, Integration, Transformation, Normalisation, Cleaning, Discretization, and Binning
Data Cleaning involves the identification and correction of errors, outliers, duplicates, or inconsistencies in raw data to improve its quality, aiming to eliminate noise and irregularities and establish a reliable foundation for subsequent analysis.
Published in Chapter: Big Data Preprocessing, Techniques, Integration, Transformation, Normalisation, Cleaning, Discretization, and Binning; From: Big Data Analytics Techniques for Market Intelligence
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Chapter 69
Data Science in the Database: Using SQL for Data Preparation
Set of activities carried out to take 'dirty' data (data with problems like missing data, outliers, etc.) and transform it into 'clean' or 'tidy' data. Its focus is on solving any issues the data may have so as to get the data ready for further analysis.
Published in Chapter: Data Science in the Database: Using SQL for Data Preparation; From: Encyclopedia of Data Science and Machine Learning
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Chapter 18
Machine Learning in Text Analysis
A sub-process in data preprocessing, where we remove punctuation, stop words, etc. from the text.
Published in Chapter: Machine Learning in Text Analysis; From: Handbook of Research on Emerging Trends and Applications of Machine Learning
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Chapter 30
A Machine Learning Approach to Data Cleaning in Databases and Data Warehouses
Data cleaning is the process of improving the quality of the data by modifying their form or content, for example, removing or correcting erroneous data values, filling in missing values, and so forth.
Published in Chapter: A Machine Learning Approach to Data Cleaning in Databases and Data Warehouses; From: Handbook of Research on Fuzzy Information Processing in Databases
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