Data Quality Feb 22, 2022. 6 Dimensions of Data Quality, Examples, and Measurement In this guide, I will explain both data quality (DQ) and the six data quality dimensions. Additionally, you will learn advanced data quality concepts, data quality measurement, and examples of different data quality dimensions. This guide shares my 25+ years of experience…
The Challenges: Today’s organizations have thousands of data integration (ETL) processes constantly moving silos of data from various operational and/or external data sources to downstream applications.
Since the downstream system doesn’t have control over incoming data or the process, it can cause serious data issues due to:
The quality of the data depends on the upstream systems,
The ETL jobs may not process the data correctly.
iCEDQ is a Quality Assurance and Test Automation platform for data-centric projects and processes such as data warehouse, CRM, data migration & conversion, ETL. It certifies the ETL processes or migration by effective ETL Testing and Data Migration Testing. The product can be further used for monitoring the data processes in production. The product emphasizes mainly process quality.
The major difference between iCEDQ & other Data Quality tools is the purpose they serve. iCEDQ is a test automation platform for process quality whereas other Data Quality tools are a combination of data profiling & fixing/ correction tool used in production.