Data Cleansing- An Alternate Approach For Handling Missing Values |
Author(s): |
| Sandeep Sahu , padmabhushan vasantdada patil pratishthan's college of engineering; Saurabh Rane, padmabhushan vasantdada patil pratishthan's college of engineering; Saurabh Sawant, padmabhushan vasantdada patil pratishthan's college of engineering; Mitali Narkar, padmabhushan vasantdada patil pratishthan's college of engineering; Prachi Kshirsagar, padmabhushan vasantdada patil pratishthan's college of engineering |
Keywords: |
| Database, Data cleansing, Data cleansing tools, Data wrangler, Missing value, Open refine |
Abstract |
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In this computer dependent world lot of data is being stored and processed every moment which also includes possibility of presence of dirty data. Data cleansing is the process of detecting and removing incorrect data from a data set. It is required while integration of data into a database or a data warehouse also known as the ETL process. A brief overview of existing data cleansing tools with their comparison is given. Most of the available tools completely ignore the records which contain any empty field which may result in an incorrect analysis. One of the solutions is to replace the missing value with a default value or an average value. |
Other Details |
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Paper ID: IJSRDV2I12418 Published in: Volume : 2, Issue : 12 Publication Date: 01/03/2015 Page(s): 744-746 |
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