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Cloud Data Quality
Quickly identify, fix, and monitor data quality problems in your cloud and on-premises business applications.
Intelligent Cloud Data Quality
Get up and running faster with comprehensive self-service capabilities that you can use across all cloud and on-premises sources.
Faster Deployment
Accelerate cloud benefits through faster migrations and gain more trusted insights from cloud data warehouses, data lakes, and SaaS applications. A modern, modular, and flexible approach to data quality helps organizations adopt new data quality patterns to keep up with market changes and stay competitive.
Greater Adoption
Insert data quality into your cloud initiatives to build trust in your data, boost adoption, and align with business needs. Quality data drives positive business outcomes such as deeper customer engagement, improved cross-sell and upsell activities, better customer segmentation, increased marketing effectiveness, and sales team productivity.
Lower Costs
Reap the budget benefits of a single, 100%-cloud-based, self-service data quality tool across all departments, applications, and deployment models, delivered as an economically priced subscription service.
Trust Your Results
With insights based on trusted data, you can increase business agility and leverage new opportunities and revenue models through quality-controlled and governed cloud data warehouse implementation.
Key Features
Informatica Cloud Data Quality’s intelligent self-service approach enables you to cleanse, standardize, and enrich all data using an extensive set of prebuilt data quality rules that includes address verification.
Rule builder for business analysts
Allows business users to build and test logical business rules without relying on IT.
Rich set of data quality transformations
Ensure delivery of high-quality information with data cleansing and standardization, verification, and enrichment capabilities.
Pre-built, reusable rules and accelerators
Accelerate projects with a comprehensive set of pre-built business rules and accelerators; reuse common data quality rules across any data from any source to save time and resources.
Exception management
Incorporate human tasks into the workflow, allowing business users to review, correct, and approve exceptions throughout the automated process.
Flexible patterns
Enrich and standardize any data from multi-cloud and on-premises sources for all use cases and for all workloads across the enterprise.
AI-powered automation
Automate generation of data quality measurements based on business rule definitions associated to a term or a critical data element.
Monitor the data
Continuously monitor and track data quality across source systems over time.
Modern API-based microservices architecture
Leverage a modular, agile approach to implementing data quality for faster integration and flexible deployment.
Customer Success Stories
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