Agile Data Warehouse Testing & Data Migration Testing
Development of a data warehouse, ETL, data migration or conversion always faces an ever-decreasing timeline. These implementations can take years to complete and users are not ready to wait that long.
The waterfall development model has been discarded in favor of the agile or development model. However, this has changed only one component of the Data Development Life Cycle. This does not mean that the quality of these processes or the data they produce is of high quality.
So what about Quality Assurance? While the developers have moved on to agile development, the QA team is stuck with the legacy approach and thus testers can’t cope with the speed that developers are delivering the ETL code.
There are primarily two reasons for this…
- Lack of Agile approach towards Quality Assurance
- Lack of Automated ETL Testing
iCEDQ is a Rules Engine for testing ETL processes. It provides a way to capture the testing requirements or “Audit Rules” for each story in parallel to the data transformation requirements.
How does iCEDQ work?
iCEDQ has a specialized rules engine for data that allow the users to validate and reconcile data across systems. It has adapters to databases, files and big data that enable it to connect and compare the data in-memory to certify the data integration or migration processes are accurate.
- Supports agile testing & development
- Automated ETL/Data Warehouse testing and data migration testing
- Replaces manual processes to improve both productivity and quality
- Collaborate and communicate with the business users
- Shortens project lifecycles and reduces project risk
- A Practical Guide for Data Centric Testing: Automated ETL Testing
- Overcome Data Testing Challenges
- Agile Data Warehouse Testing & Data Migration Testing
- Migrating Database to Redshift, Snowflake, Azure DW and Test with iCEDQ
- Data Migration Testing Techniques to Migrate Data Successfully
- The Data Migration Process & the Potential Risks
- DataOps Implementation Guide
- AML Software Implementation & Production Monitoring with iCEDQ DataOps Platform
- What Are The Challenges Of A Data Factory