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Table 3 Challenges and solutions
From: Dynamic-ETL: a hybrid approach for health data extraction, transformation and loading
| Challenges | Solution by D-ETL Approach |
|---|---|
| Heterogeneity in source data sets | • ETL specifications • Rule-based D-ETL engine • Native SQL code acceptance • Custom rule mechanism |
| Data extraction interferes with source EHR | • CSV file format |
| Efficiency | • Integrated D-ETL engine • Query optimization |
| Duplicate and overlapping data | • Automated data de-duplication and incremental data loading |
| Data quality | • Input data: Extracted data validation • Output data: Data profiling and visualization |
| Human expertise | • Explicit rule structure • Effective rule testing and debugging mechanism |
| Resumption (ability to continue from a point where an error previously occurred) | • Modular ETL process |
