Initial ETL Data Validation
Content
DOV: Data Validation
Initial ETL Data Validation Enterprise Data Integration development is a difficult and expensive process, which can take many months or even years. Fundamentally, the quality of the data integration development is only as good as the quality of data it produces, making proper data validation critical. Once the ETL development is complete, source and target data need to be compared to ensure that the data in the target is accurate, complete and was transformed correctly. The comparison between source and target data include record counts, field totals, joins, lookups and many others. DataValidator’s extensive library of tests allows developers and business analysts to ensure that the data loaded into a target is both correct and 100% complete.
Ongoing ETL Data Validation Ongoing ETL Data Validation Data Validation does not stop once the development phase is over. Every incremental data load needs to be checked to ensure that it is correct and complete. DataValidator makes it easy to reuse the existing data validation rules set up during the development phase to perform incremental data validation. PowerCenter Version Upgrades Upgrading PowerCenter to the latest version can be a time-consuming and expensive process due to the data validation required to ensure that the data produced by the latest version is identical to what is being generated by the production version. An enterprise-level implementation often has hundreds of tables, thousands of fields, and terabytes of data, making it impossible to manually validate all data. IT professionals face the difficult task of deciding which data to spot check, and then hope that the data not checked is correct. Even once the initial data validation is complete and the new version goes into production, it is often run in parallel with the old version, making incremental data validation a necessity as well.
DOV: Data Validation
DataValidator dramatically reduces the time and cost of PowerCenter upgrades by automatically generating and running all necessary tests to validate 100% of the data and to identify and display every single discrepancy between production and development databases.
Database Version Upgrades Upgrading a database to a new version also requires extensive data validation to make sure that both databases are identical. Once the new database version is up and running in development, DataValidator will automatically generate and run tests to make sure that the new version is 100% identical to the one currently in production.
Runtime ETL Validation, Reconciliation and Audit-Balance-Control Solutions Data Validation checks often need to be performed as part of the production, rather than testing process. For example the staging to target load can only proceed if all the validation checks of source vs. staging data have passed. DataValidator can be embedded into the ETL workflow or any other process to perform sophisticated runtime data checks, thus becoming an integral part of any reconciliation or auditbalance-control solution.
Initial ETL Data Validation Enterprise Data Integration development is a difficult and expensive process, which can take many months or even years. Fundamentally, the quality of the data integration development is only as good as the quality of data it produces, making proper data validation critical. Once the ETL development is complete, source and target data need to be compared to ensure that the data in the target is accurate, complete and was transformed correctly. The comparison between source and target data include record counts, field totals, joins, lookups and many others. DataValidator’s extensive library of tests allows developers and business analysts to ensure that the data loaded into a target is both correct and 100% complete.
Ongoing ETL Data Validation Ongoing ETL Data Validation Data Validation does not stop once the development phase is over. Every incremental data load needs to be checked to ensure that it is correct and complete. DataValidator makes it easy to reuse the existing data validation rules set up during the development phase to perform incremental data validation. PowerCenter Version Upgrades Upgrading PowerCenter to the latest version can be a time-consuming and expensive process due to the data validation required to ensure that the data produced by the latest version is identical to what is being generated by the production version. An enterprise-level implementation often has hundreds of tables, thousands of fields, and terabytes of data, making it impossible to manually validate all data. IT professionals face the difficult task of deciding which data to spot check, and then hope that the data not checked is correct. Even once the initial data validation is complete and the new version goes into production, it is often run in parallel with the old version, making incremental data validation a necessity as well.
DOV: Data Validation
DataValidator dramatically reduces the time and cost of PowerCenter upgrades by automatically generating and running all necessary tests to validate 100% of the data and to identify and display every single discrepancy between production and development databases.
Database Version Upgrades Upgrading a database to a new version also requires extensive data validation to make sure that both databases are identical. Once the new database version is up and running in development, DataValidator will automatically generate and run tests to make sure that the new version is 100% identical to the one currently in production.
Runtime ETL Validation, Reconciliation and Audit-Balance-Control Solutions Data Validation checks often need to be performed as part of the production, rather than testing process. For example the staging to target load can only proceed if all the validation checks of source vs. staging data have passed. DataValidator can be embedded into the ETL workflow or any other process to perform sophisticated runtime data checks, thus becoming an integral part of any reconciliation or auditbalance-control solution.
