> ## Documentation Index > Fetch the complete documentation index at: https://docs.skypoint.ai/llms.txt > Use this file to discover all available pages before exploring further. # # 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 skyMDM automatically suggests validation types based on column names and data patterns. Apply email, phone, date, ZIP code, and custom validations to your columns. See the percentage of valid records for each column and validation type. Monitor how validation scores change over time as data quality improves. ## Validation Types Verify email format, domain validity, and deliverability indicators Check phone number format, valid area codes, and number type (mobile, landline) Validate date formats, reasonable ranges, and logical consistency Verify ZIP codes exist and match expected geographic regions Parse and validate address components for deliverability 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 Validated contact information increases successful patient communications. Catch data issues before they impact clinical or operational workflows. 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