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Prioritize Security Posture Remediation
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Prevent Unauthorized Access to Sensitive Data
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Monitor Data Risk
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Analyze Data Breach Impact
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Data Integration
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Pipeline Designer
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Data Inventory
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Truly trust your data - As an integral part of Talend Data Fabric, Data Quality profiles, cleans, and masks data in real-time.
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Automate better data - Data profiling lets you quickly identify data quality issues, discover hidden patterns, and spot anomalies
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Free up data workers to focus on what matters - Cleanse incoming data with ML-enabled deduplication, validation, and standardization.
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Protect your assets and prioritize compliance - Protects sensitive data with built-in masking, ensuring compliance, data privacy and data protection regulations.
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Deliver trusted data to the people who need it
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A unified approach to data integrity and governance
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Data Catalog
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Data Inventory
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Don’t waste another minute on one-off integrations - With Talend, you can share services and trusted data across internal departments and external groups with user-friendly APIs. Streamline DevOps and lower operational costs by implementing APIs and microservices, which teams can reuse to build new projects instead of reinventing the wheel each time.
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A unified approach to application and API integration - Talend Data Fabric gives you everything you need to meet the real-time demands of the business with APIs and event-driven architectures. Use a unified platform for API development, application, and data integration, and data quality to increase team productivity and deliver solutions to the market faster.
Talend is the first and only company to combine data integration and data integrity in a single platform. Bring together people, data, and machine learning technology to easily access, monitor, and fix your data. The Talend Trust Score gives you at-a-glance visibility into the reliability of any dataset, so you can put healthy data at the center of business, move faster, and make better decisions.
To achieve data trust in a world drowning in so much data, organizations must implement and automate processes for auditing, assessing, and cleaning their data. But data trust can’t be accomplished through technology alone. Complete data trust solutions require data infrastructure that considers human processes along with software. It's necessary to create a data-centric culture that works in concert with data quality automation.