ENTERPRISE DATA QUALITY PLATFORM
It's time to finally be confident in your data
Automate and refine data quality controls with advanced machine learning, minimizing manual effort while delivering data confidence.
Seamless integration with your data stack
enterprise Data quality challenges
Managing enterprise data quality at scale is challenging
Data quality is reactive
Data Quality is often driven by end users spotting bad data points. We need to be proactive about our data quality.
Teams aren't collaborating
Subject matter experts know their data the best – but rely on data teams to deliver high quality data. Business teams and data teams need to collaborate and co-own data quality.
Lack of measurement
We can’t improve what we don’t measure. We need a comprehensive way of establishing a baseline for and measuring impact of data quality across the data ecosystem.
Qualytics for enterprise data teams
Continuous Improvement for Data Quality
Consolidate all data quality management activities
Centralized Repository of all data quality rules – technical data quality to complex business logic – in one place
Scalable and flexible runtime environment
Scalable Runtime Environment that scales to enterprise-grade scale, drives downstream remediation workflows and measures impact of DQ
Automate generation and maintenance of data quality rules
Rules are generated, suggested and updated by Qualytics’ AI engine by analyzing historic data’s shapes and patterns, reducing the effort to manage data quality at enterprise scale by over 90%.
Data teams after qualytics
How your team benefits
Automated rules
Automated rules reduce the effort of writing rules for expectations and calibration by over 90%. Qualytics utilizes our inference engine to proactively profile and subsequently generate data quality rules by training on historic datasets.
Centralized management
Centralized rule repository for all technical and business data quality rules gives a single pane of glass for all expectations and calibration for fit.
Save hours of work
Easy downstream remediation workflow initiation and Enrichment capabilities remove the need to replicate work to hunt for anomalies, significantly reducing the time to resolution and elevating explainability & root cause analysis
Ease of use
Highly usable interface superserves business users to be involved in DQ, while the fully fledged API superserves data engineers to automate workflows within their existing data tooling.
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