KS Validatum is a powerful data quality and observability platform designed to ensure your data is accurate, reliable, and consistent. Our product enables businesses to monitor and maintain data integrity in two distinct modes. Within an individual database or system, and across multiple systems when data is transformed or transferred between them. By proactively identifying and assisting in resolution of data quality issues, KS Validatum reduces risks, improves decision-making, and strengthens data governance.
Key Features
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Ensure Data Integrity Across Your Organization
KS Validatum proactively detects and assists in resolving data integrity issues before they impact business operations. It scans for inconsistencies, orphaned records, constraint violations, and structural anomalies that compromise data reliability. With continuous monitoring of both technical constraints and business rules, organizations can maintain high-quality data standards, ensuring confident decision-making.
Seamless Integration with All Data Sources
KS Validatum connects effortlessly with a wide range of data repositories, including SQL Server, MySQL, Oracle, PostgreSQL, and various file formats. This broad compatibility ensures enterprise-wide data quality enforcement, eliminating blind spots and maintaining consistency across all platforms.
Advanced Validation with Numeric, Set-Based, and Statistical Comparators
KS Validatum offers multi-layered validation mechanisms to assess data from different perspectives
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Numeric checks verify compliance with thresholds and expected ranges.
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Set-based validation ensures referential integrity and consistency across datasets.
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Statistical comparators detect anomalies and outliers, identifying patterns of potential data corruption.
These flexible validation methods ensure adherence to enterprise-wide data quality policies.
Cross-Database Data Comparison & Discrepancy Detection
KS Validatum excels in comparing data across multiple sources, ensuring unmatched data integrity. Its advanced comparison capabilities detect discrepancies, enabling seamless synchronization between systems. By continuously monitoring data and providing observability, it offers a comprehensive view of data consistency. KS Validatum helps businesses maintain accuracy, reliability, and trust in their data.
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AI-Powered Rule Generation for Faster Implementation
Leverage AI-driven intelligence to automate and optimize data validation rule creation. KS Validatum analyzes data structures and patterns to recommend tailored validation rules, reducing manual effort and ensuring comprehensive quality checks. This self-learning capability accelerates implementation while enhancing data governance.
Industry & Database Agnostic for Maximum Flexibility
Designed for cross-industry adaptability, KS Validatum supports finance, healthcare, retail, and more. As a database-agnostic solution, it integrates seamlessly with SQL Server, MySQL, Oracle, PostgreSQL, and various file formats, ensuring a unified approach to data quality management without platform limitations.
KS Validatum Workflow
Configure or Add Data Source
Set up and integrate various data sources, such as databases and files, to facilitate data extraction. This is the first step in assessing data quality .
Configure Source and Target
Define and map the source and target data sources to facilitate accurate data comparison. This step ensures seamless integration by specifying database connections, tables, and columns for validation.
Configure Rules & Expressions
Establish rules and expressions to assess data consistency, accuracy, and validity. These rules help identify discrepancies and enforce business logic to maintain high data quality.
Scheduling
Automate the execution of validation rules by setting up schedules at any desired time. This ensures timely data quality checks without manual intervention.
Execution of the Rules
Execute the configured rules to validate data integrity, detect anomalies, and ensure compliance with predefined standards.
Results Back to Dashboard
Present processed data insights on an interactive dashboard for real-time analysis and decision-making. This step helps users track data quality trends and take necessary corrective actions.