Data mining and data cleaning

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18450%2F05%3A00001714" target="_blank" >RIV/62690094:18450/05:00001714 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Data mining and data cleaning
Original language description
This paper deals with the importance of data quality in the data mining process. Organizations rely upon their data from which information and knowledge are produced for business decision-making. The quality of the results achieved through analysis is highly correlated with the quality of the inputs - data. The efficient implementation of the data mining algorithms and the interpretation of the results are of little value unless any techniques to detect and remove bad data are applied. There are many different ways how the data can become bad. It can be inaccurate, inconsistent, incomplete and out of date. Data can be also changed both deliberately or accidentally. Bad data results in wrong decision-making, which can damage the business, therefore datacleaning should be an integral part of analysis. The organizations with cleaner data and the means to use that data will gain a competitive advantage. The techniques to help ensure data quality by data cleaning and applying data quality
Czech name
Data mining a kvalita dat
Czech description
data mining, kvalita dat, čištění dat, See5

Project
<a href="/en/project/GA402%2F04%2F1308" target="_blank" >GA402/04/1308: Classification models and the assessment of their predictive properties</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2005
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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