How to reduce data inconsistency with effective DataOps
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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.