Identify, Correct, and Prevent data quality issues
Like termites eating away at the structure of your home, data quality issues are only noticed once they’re causing a problem.
Instead of fixing them after the fact, data quality rules identify bad data, allowing data stewards to proactively correct them before they create a problem.
When data quality becomes an issue, the solution is often a data cleanup project. But once complete, poor quality will again be created, creating a vicious cycle.
Stop wasting time on-off data clean-up projects. With Profisee, you can permanently identify, correct, and prevent data quality issues.
Similar to an Excel spreadsheet, data can often be calculated automatically based on other information instead of manually entered.
Assignment and default rules take the burden off of data stewards, and allow the system to create information automatically based on rules you define.
Business rules provide a simple user friendly way to define and enforce data quality.
Automate the calculation of values, identify data quality issues, or use constraints to prevent bad data from being created, all using a single business rules framework.
Simple Excel like syntax allows rules to be managed by business users.
Identifies and highlights data quality issues, allowing them to be corrected proactively by data stewards.
Data quality heat maps and analytics provides stakeholders with visibility into data quality trends.
Data Quality Constraints
Configure constraint rules to prevent users from creating or update records that don’t meet a minimum threshold of quality. Define default rules to pre-populate new records with data, saving stewards time.
Help data stewards create high quality information with minimal effort.
Discover the success Profisee has brought to companies like yours.
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