Ensure every dataset is accurate, complete, and ready for analytics and AI. Qlik continuously monitors, enriches, and validates data quality across all sources and environments – detecting issues early and enabling fast remediation. The result: data you can trust, analytics you can rely on, and AI that delivers
Build trusted, governed data with Qlik Talend Cloud
Data Quality & Governance
Continuously monitor and elevate data quality across all systems by detecting missing values, inconsistencies, duplications, and errors. Built-in rules automate remediation workflows, ensuring that only trusted, verified data is shared. With data governance embedded directly into the pipeline, consistency and control are maintained seamlessly across the entire data ecosystem
- Detection of missing, invalid, or duplicated data
- Automated remediation processes
- Standardized data across systems
Measurable Trust
Get a clear, real-time picture of data reliability with Qlik Trust Score™ — a measurable, structured approach to data quality. Through automated data profiling, pipelines are continuously assessed against defined quality dimensions, helping teams identify issues early, prioritize fixes, and track improvements over time.
- Clear data quality scoring
- Real-time visibility into dataset trust levels
- Prioritized data issues based on impact
Smarter Analytics & More Powerful AI
Ensure every dataset is complete, governed, and ready for analytics and AI by combining unified data governance with a centralized metadata catalog. Together, they create a consistent, organization-wide view of data – boosting analytics adoption and driving better business outcomes.
- Complete, analytics – and AI-ready datasets
- Unified metadata across the organization
- A consistent, trusted single source of truth
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How Teams Solve Their Data Challenges
Data Analyst
Data Analyst
Data Steward
Data Steward
AI Lead
AI Lead
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FAQs
Data governance defines the policies, ownership, security, and management processes surrounding data. Data quality focuses on the accuracy, consistency, completeness, and reliability of the data itself.
A data catalog provides a centralized inventory of datasets, metadata, lineage, and business context. It helps teams discover, understand, and trust data more easily for analytics, reporting, and AI initiatives.
Qlik supports compliance initiatives through governance controls, auditability, data lineage, role-based access management, and data masking capabilities that help organizations manage sensitive information securely.
Qlik Talend Trust Score™ evaluates datasets across multiple quality dimensions including completeness, validity, usage, and reliability, providing a measurable indicator of overall data trustworthiness.
Data lineage tracks how data moves and changes across systems and pipelines. It helps teams understand data origins, transformations, dependencies, and reliability, which is critical for trusted analytics and AI outcomes.
Yes. Qlik continuously profiles and monitors datasets to identify inconsistencies, missing values, duplications, and other quality issues across the data lifecycle.
Centralized metadata provides a consistent organizational view of datasets, definitions, ownership, and lineage, helping improve collaboration, governance, and trust across teams and systems.