Manage The Quality Of Your Data From Start To Finish

Identify, Correct, and Prevent data quality issues

Proactive Prevention

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.

Permanent Correction

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.

Automated Assignments

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.

Business Rules

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.

  • Assignment rules to calculate values
  • Validation rules to flag issues
  • Constraint rules to prevent bad data

Validation Issues

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.

  • Flag poor quality information
  • Enable stewards to proactively resolve
  • Measure improvement over time

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.

  • Prevent bad data with constraints
  • Share data quality requirements with stewards
  • Pre-populate data, saving time

Business Problems Solved With Master Data Management

Discover the success Profisee has brought to companies like yours.

Case Study
Needed Master Data to Optimize Sales & Profit

How Profisee helped Domino’s Pizza achieve their Insight Driven Enterprise.

Read more.

Case Study
Customer, vendor, materials data across 3 SAP instances

Learn how ITT created a single source of truth across customer, vendor and materials data.

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Case Study
Mastering Product and Customer to revolutionize their business process efficiency

See how Ready Mix USA used MDM to fill holes in their reporting and analytics.

Read more.

Case Study
Managing Customer Data in High Growth Mode

Learn how Ossur reduced shipping costs and addressed data quality across 10 systems.

Read more.

Case Study
Needed Accurate and Timely Data Updates

See how GAP achieved a 50% reduction in manual effort to update their financial reports.

Read more.

Case Study
M&As caused lack of business insight across facilities

See how this healthcare company used MDM to improve visibility into facility operations and profitability.

Read more.

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