- Testing is still completely underrated in the data world. Still, almost all data developers shy away from testing.
- Data teams don’t implement tests in the right places and data issues are caught by end-users
- Data Tests not implemented in the right places
This session will show the audience the WHY, WHERE, and HOW to do data testing and validation before working on any data-driven project using AI and ML-infused emerging concepts and tools.
Takeaways from the talk:
- What is Data Testing and Data Validation
- Why is Data Testing and Data Validation Important
- How to do Data Testing Data Validation from end to end
- Processes/tools / Technologies and Vendors in this Space
- Synthetic data generation capabilities for data testing
- You will walk away with a very good idea of all the above points with respect to data testing and validation and eventually data quality