The extraction, transformation and loading (ETL) of data is the key to success in a BI system that lets you manage the quality of the data properly.
- We Ensure the cleanliness and quality of their data by using powerful ETL and Data Quality solutions.
- Experts in integrating all sources of data, transactional, unstructured, external ... creating consistent patterns in the organization.
Best practices we recommend for the design of ETL processes:
- Centralization of procedures, so as to ensure coherence and consistency of the exchanged data from different sources.
- Avoid redundancy of calculations: if there is data previously calculated in the operational databases should not be re-calculated in the extraction. This premise seeks to achieve two objectives:
1.- Improve process performancec.
2.- Avoid possible inconsistencies between the results of operational systems and those obtained in the DW.
- Establishing points of "quality control" and validation:
1.- Technical: ensuring the correct execution of processes.
2.- Functional: reports generically to validate the data entered.
- Implement processes charging information, possible errors in the initial information.
- Consider the possibility of intermediate tables using the atomic level of information to be treated.