How to reduce data inconsistency with effective DataOps
If your DataOps process is not well understood, it is likely leading to inconsistencies that can cause your customers to question the quality of your data, along with other challenges, including:
- Changes that break something in production
- The speed to delivery for enhancements
- Reintroducing repeated bugs on future deployments
- And human error and cost
Access this blog post to learn more about these 4 potential implications of ineffective DataOps & discover strategies for evaluating the =current state of your process.