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DATA CLEANING 3
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DATA CLEANING 3
Why need to clean data?
- Because Data quality may be compromised by:
- Inconsistent data
- What cause it?
- Because of changes in the coding system
- EGs
- The coding of the products for a company may be revised at a certain date.
- When the data before this date is merged with the recorded data, data inconsistencies result if the data before the change are not recoded to the new coding scheme.
- The coding of the products for a company may be revised at a certain date.
- EGs
- Because of changes in the coding system
- What to do?
- 1. IDENTIFY anomalous data or outliers
- HOW to identify?
- To examine the statistics in the Data Audit page
- OR apply Unsupervised CLUSTERING method
- Slides
- Isolated points far from cluster centres are likely to be outliers
- Slides
- HOW to identify?
- 2. Subsequently correct or eliminate them
- 1. IDENTIFY anomalous data or outliers
- What cause it?
- Inconsistent data
- Because Data quality may be compromised by:
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- Data Mining Mind Map on DATA CLEANING 3, created by sue san on 05/02/2017.
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- sue san
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- Created by sue san · Feb 5, 2017
- Copied by sue san · Feb 5, 2017
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