ENTERPRISE DATA QUALITY
Deliver Trusted, Accurate Data with Qlik's Enterprise Data Quality Platform
Improve accuracy, consistency, and trust in your data with comprehensive quality management. Automate data validation, cleansing, and governance to deliver analytics-ready insights across the enterprise.
Improve business outcomes with consistent, high-quality data
Establish enterprise-wide data quality that ensures every decision, analysis, and operational process relies on accurate, validated information through comprehensive quality management and governance.
Identify and eliminate duplicates, gaps, and inconsistencies
Detect quality issues automatically with intelligent profiling that discovers duplicates, identifies missing data, and flags inconsistencies across massive datasets without manual inspection.
Enforce governance and data quality standards automatically
Apply quality rules consistently across the enterprise with automated validation that ensures data meets standards before reaching analytics, reports, or operational systems.
Empower teams with reliable data for analytics and AI
Enable confident decision-making and accurate AI models with high-quality data that eliminates the garbage-in-garbage-out problem plaguing analytics and machine learning initiatives.
How Qlik's Enterprise Data Quality Platform works
Step 1 - Connect to diverse data sources across your enterprise
Step 2 - Profile, cleanse, and enrich data at scale
Step 3 - Apply validation rules and business logic
Step 4 - Deliver accurate data to analytics and business systems
Why choose Qlik for enterprise data quality
Quality integrated with data integration
Combine data quality with integration, governance, and analytics capabilities in a unified platform that streamlines end-to-end data management and ensures quality throughout workflows.
Continuous quality without manual intervention
Monitor data quality continuously with automated workflows that detect issues, apply corrections, and alert stakeholders without requiring manual monitoring or intervention.
Quality everywhere data flows
Embed quality controls within existing workflows, connecting with data warehouses, lakes, analytics platforms, and governance tools to ensure consistency across the data ecosystem.
Quality that supports regulatory compliance
Demonstrate data quality compliance during audits with comprehensive documentation of quality rules, validation results, and correction actions that satisfy regulatory requirements.
Trusted for mission-critical data quality
Join organizations that improved analytics accuracy, reduced operational errors, and enabled AI initiatives by establishing enterprise data quality with Qlik's platform.
Key capabilities of Qlik's Enterprise Data Quality Platform
AI-assisted data profiling and cleansing
Analyze data distributions, identify patterns, and detect quality issues automatically with machine learning that understands data semantics and recommends appropriate corrections.
Advanced matching, deduplication, and standardization
Identify duplicate records across sources using fuzzy matching and probabilistic algorithms while standardizing formats, addresses, and names to enterprise conventions.
Centralized quality dashboards and monitoring
Track quality metrics, issue trends, and improvement progress through unified dashboards that provide visibility into data quality health across the enterprise.
Data enrichment through third-party and cloud sources
Enhance internal data with external information from reference data providers, cloud services, and public sources to add missing attributes and validate accuracy.
End-to-end governance and lineage tracking
Track quality issues from origin through resolution with complete lineage that shows how quality problems propagate and where corrections were applied.
Secure, scalable architecture for enterprise environments
Process billions of records with distributed quality processing that maintains performance at enterprise scale while protecting sensitive data during quality operations.
Trusted by leading enterprises worldwide
What our customers say
We needed to consolidate data in one place, from heterogeneous sources, updated in almost real-time. That’s what Qlik enables for us.
Connect to 500+ data sources with Qlik’s analytics integrations
SAP
Adobe
IBM
AWS
MySQL
Jira
Azure
MS SQL
Apache
Mongo DB
SAP
Adobe
IBM
AWS
MySQL
Jira
Azure
MS SQL
Apache
Mongo DB
SAP
Adobe
IBM
AWS
MySQL
Jira
Azure
MS SQL
Apache
Mongo DB
SAP
Adobe
IBM
AWS
MySQL
Jira
Azure
MS SQL
Apache
Mongo DB
SAP
Adobe
IBM
AWS
MySQL
Jira
Azure
MS SQL
Apache
Mongo DB
Oracle
Salesforce
Workday
Apache Iceberg
CircleCI
Zendesk
Snowflake
Databricks
OpenAI
Intuit
Oracle
Salesforce
Workday
Apache Iceberg
CircleCI
Zendesk
Snowflake
Databricks
OpenAI
Intuit
Oracle
Salesforce
Workday
Apache Iceberg
CircleCI
Zendesk
Snowflake
Databricks
OpenAI
Intuit
Oracle
Salesforce
Workday
Apache Iceberg
CircleCI
Zendesk
Snowflake
Databricks
OpenAI
Intuit
Oracle
Salesforce
Workday
Apache Iceberg
CircleCI
Zendesk
Snowflake
Databricks
OpenAI
Intuit
Resources
Enterprise Data Quality FAQs
Enterprise quality establishes consistent standards, rules, and processes across all data assets rather than applying isolated quality controls to individual datasets or applications.
Yes, machine learning continuously monitors data patterns and adapts quality rules automatically while alerting administrators to significant changes requiring human review.
Automated quality handles standard issues confidently while flagging ambiguous situations for human review, with confidence scores that help prioritize manual intervention efforts.
The platform detects duplicates, missing values, format inconsistencies, referential integrity violations, outliers, and business rule violations through comprehensive profiling and validation.