An amazing platform to transform data, ensure quality, and automate robust data pipelines
Use Cases and Deployment Scope
Pros
- It provides ability to profile, discover, and validate data quality.
- It allows to drill down into larger amounts of data.
- It automatically suggests possible quality rules based on a statistical profile of the data.
Cons
- It can expand connectivity to apply adaptive data quality rules to any data source.
- It can employing more advanced transformation techniques to transform data for specific formats.
- It can further continue on its existing capabilities like providing more enriched data curation.
Most Important Features
- Data profiling
- Ongoing data quality assesment
- Visual guidance
Return on Investment
- Accelerated data transormation
- Increase collaboration
- Automated processeing