Data Quality
Turn data quality from repeated manual reviews into a continuous operational system that monitors issues, measures asset quality, and alerts teams early, before inaccurate data affects reports or decisions.
Instead of manually checking data every time, quality rules and automated alerts help teams identify issues in a continuous, structured way.
Continuous monitoring identifies data quality issues early, before they appear in dashboards or affect decisions made by leadership and operational teams.
When data is accurate and complete, reports become more dependable, and decisions are built on a clear foundation instead of numbers that need repeated validation.
High-quality data makes assets more auditable and supports compliance evidence through clear indicators and a documented quality record.
From data profiling and quality rule creation to issue alerts and performance tracking, Governata Data Quality gives your organization a structured, measurable way to monitor and continuously improve the quality of its data.
The starting point of quality management is understanding current data, then defining how to measure it. These modules automatically profile your data and build executable quality rules.
Data Profiling "Soon"
Comprehensive automated scanning of tables for row, value, and distribution metrics.
Quality Rules "Soon"
Build executable rules on accuracy, completeness, consistency, and timeliness per asset.
Once rules are defined, continuous monitoring begins. These modules display quality status in real time and generate structured reports for every quality indicator.
Quality Dashboard "Soon"
Real-time view of data quality with tracking of most-affected assets.
Quality Reports "Soon"
Structured reports showing improvements, declines, and priorities for teams and decision-makers.
Complete framework to organize, classify, and track your data
A unified and fully trusted source for your core data across all enterprise systems
Organized and reliable data movement between your systems
Personal data discovery and protection under PDPL
Comprehensive administrative backbone running Governata across your organization
Safe system connection and automatic metadata discovery
Unified reference for code sets, hierarchies, and values
Smart search in plain language for trusted answers
The system scans data assets and extracts key indicators such as missing values, value distribution, top values, and data samples to build a clear view of the current quality state.
Quality rules are defined for each data asset based on the dimension being measured, such as accuracy, completeness, timeliness, consistency, or relevance, with clear thresholds and monitoring frequency.
The system continuously tracks quality indicators and sends alerts when accepted thresholds are exceeded, allowing teams to intervene before issues reach reports or decisions.
Governata Data Quality goes beyond detecting errors. It connects measurement, monitoring, and early alerts in one workflow that helps teams continuously improve data quality.
Measurement
Clear quality indicators for every data asset
Measure accuracy, completeness, timeliness, consistency, and relevance through trackable indicators, instead of relying on assumptions or manual review.
Monitoring
Continuous visibility instead of periodic checks
Monitor data quality on a scheduled basis or whenever assets are updated, so teams can identify quality decline before it affects reports or operations.
Improvement
Clear priorities for issue resolution
Identify the most affected assets, understand severity levels, and guide teams to address the highest-impact issues first instead of working reactively or randomly.
Instant connection to systems and existing data sources within your organization without the need to change your infrastructure.
No. The program presents clear indicators and shows where the issue exists and what its potential impact may be, allowing data and governance teams to monitor quality without writing queries or running manual checks every time.
Quality rules are created by selecting the data asset, choosing the quality dimension to measure, setting the accepted threshold, defining the monitoring frequency, and activating alerts when accepted limits are exceeded.
Governata Data Quality supports key dimensions such as accuracy, completeness, timeliness, consistency, and relevance, with each dimension helping identify a different type of quality issue.
Yes. Quality rules can be customized based on the nature and use of each data asset, since quality standards for financial reports may differ from those for customer data or operational data.
By continuously monitoring quality indicators and sending alerts when accepted limits are exceeded, before issues reach reports or affect decisions.
Yes. Data Quality connects with the Data Catalog, Data Classification, Data Lineage, and Personal Data, so quality indicators appear within the right asset context and support governance and compliance.
Data cleansing usually fixes an existing issue as a temporary or separate action. Data quality is an ongoing process that uses rules, indicators, and alerts to prevent recurring issues and monitor them continuously.
Continuously monitor your data, apply clear quality rules to every asset, and catch issues early before they affect reports or business decisions.
