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Validate

Ensure your data meets quality standards before it flows into downstream systems. The Validate module applies intelligent validation rules to detect invalid emails, malformed phone numbers, incorrect dates, and other data quality issues.

Why Validation Matters

Clean data isn’t necessarily valid data. A phone number might be properly formatted but contain an invalid area code. An email might look correct but use an impossible domain. A date might be formatted correctly but represent an impossible value. Validation catches these issues before they cause problems:
  • Invalid contact information leads to failed patient outreach
  • Incorrect dates create scheduling conflicts and compliance issues
  • Bad data propagates through systems, compounding errors
skyMDM’s Validate module provides comprehensive data validation at scale.

What You Can Do

Auto-Detect Validation Types

skyMDM automatically suggests validation types based on column names and data patterns.

Validate Multiple Types

Apply email, phone, date, ZIP code, and custom validations to your columns.

View Quality Scores

See the percentage of valid records for each column and validation type.

Track Trends

Monitor how validation scores change over time as data quality improves.

Validation Types

Email Validation

Verify email format, domain validity, and deliverability indicators

Phone Validation

Check phone number format, valid area codes, and number type (mobile, landline)

Date Validation

Validate date formats, reasonable ranges, and logical consistency

ZIP Code Validation

Verify ZIP codes exist and match expected geographic regions

Address Validation

Parse and validate address components for deliverability

Custom Patterns

Define regex patterns for organization-specific validation needs

Key Capabilities

Intelligent Column Detection

skyMDM analyzes column names and sample data to automatically suggest appropriate validation types. Columns named “email” or “phone” are detected and pre-configured.

Validation Statistics

After validation runs, detailed statistics show exactly how your data performed—valid counts, invalid counts, null counts, and percentage breakdowns.

Column Profiling Integration

Validation builds on the column metadata from cleaning, providing a complete picture of data quality from basic statistics to semantic validation.

Scalable Execution

Validation jobs run on Databricks, handling millions of records with efficient parallel processing.

Business Impact

Improve Outreach

Validated contact information increases successful patient communications.

Reduce Errors

Catch data issues before they impact clinical or operational workflows.

Build Confidence

Stakeholders trust data backed by validation metrics and quality scores.

Who Benefits

  • Patient Access Teams: Ensure contact information is valid for appointment reminders and outreach
  • Marketing Teams: Improve campaign effectiveness with validated email and phone data
  • Quality Assurance: Track and report on data quality metrics across the organization
  • Data Engineers: Identify data quality issues at the source for upstream fixes