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Message type: E = Error
Message class: RSAN_RT - Messages for Runtime Analysis
Message number: 303
Message text: Number of complete data records for the linear regression: &1
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RSAN_RT303
- Number of complete data records for the linear regression: &1 ?The SAP error message RSAN_RT303, which states "Number of complete data records for the linear regression: &1," typically occurs in the context of SAP BW (Business Warehouse) or SAP HANA when performing linear regression analysis. This error indicates that the number of complete data records available for the regression analysis is insufficient.
Cause:
- Insufficient Data: The primary cause of this error is that there are not enough complete data records (i.e., records without missing values) for the linear regression analysis to be performed. Linear regression requires a certain number of data points to produce reliable results.
- Data Quality Issues: Missing values in the dataset can lead to a reduced number of complete records. If the dataset has many null or invalid entries, it can trigger this error.
- Filtering Conditions: If there are filters applied to the dataset that exclude a significant number of records, it may result in too few complete records for analysis.
Solution:
- Check Data Completeness: Review the dataset to ensure that it contains a sufficient number of complete records. You can do this by checking for missing values in the relevant fields.
- Data Cleansing: If there are missing values, consider cleansing the data. This can involve:
- Filling in missing values using imputation techniques.
- Removing records with missing values if they are not critical.
- Adjust Filters: If you are applying filters to the dataset, consider adjusting them to include more records. Ensure that the filters do not exclude too many relevant data points.
- Increase Data Volume: If possible, increase the volume of data being analyzed. This could involve aggregating data from different sources or extending the time period of the data being analyzed.
- Review Regression Parameters: Ensure that the parameters and settings for the regression analysis are appropriate for the dataset being used.
Related Information:
By addressing the underlying data issues and ensuring that there are enough complete records, you should be able to resolve the RSAN_RT303 error and successfully perform linear regression analysis.
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