Caninsoft's self-serve validation engine lets business users define rules, compare datasets, and surface data errors automatically — without SQL, scripts, or IT dependency.
Data validation is the process of ensuring that information entering or moving through your systems is complete, accurate, consistent, and usable. When validation fails — silently or visibly — the consequences ripple outward: wrong reports, failed feeds, compliance gaps, and decisions made on bad information.
Caninsoft puts validation directly in the hands of the people who understand the data best: your operations managers, data stewards, and business analysts. No waiting for IT. No writing queries. No spreadsheet comparisons done by hand.
Connect to your data sources — databases, flat files, APIs, or data warehouses. No complex setup required.
Use an intuitive rule builder to define what "good" data looks like for your business. Set conditions for completeness, format, range, referential integrity, and more.
Execute validation runs on demand or on a schedule. Review results in a clear dashboard. Drill into failures, understand root causes, and assign fixes — all without leaving the platform.
Define custom validation rules using plain-language conditions. No SQL required.
Compare two datasets side by side and surface every discrepancy.
Identify missing, null, or empty values across any field or column.
Enforce data types, character lengths, date formats, and pattern rules.
Set validation to run automatically — daily, weekly, or on a trigger.
Every validation run is logged with timestamps, rule versions, and user actions.
How comprehensive is your data? Ensuring all necessary information is present with no missing values.
Does your data reflect real-world conditions as per your business needs? Catch values that exist but are factually wrong.
Is your data in sync across different systems and datasets? Detect relational inconsistencies before they cause downstream failures.
How consistent is your data when it comes to format, data types, length, and special characters? Enforce structural rules automatically.
Is unnecessary or outdated information slowing down your validation process? Focus rules on what actually matters to your business.
Is the right information available when it's needed? Ensure data is current and not stale when decisions are made.
Own data quality rules without depending on engineers to write them.
Catch data errors before they affect business processes or reports.
Meet regulatory data accuracy requirements with auditable validation runs.
Validate source data before building reports, models, or dashboards.
reduction in time spent on manual data validation
coding required to define and run validation rules
detection of data issues — before they reach reports or downstream systems
logs for every validation run