FenDQ

FenDQ is a no-code data quality engine for buy-side firms. It helps teams validate market, reference, static, sustainability, alternative, and client data across existing systems.

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FenDQ was designed to rapidly shine a light on data quality across existing systems and data bases without changing your current technology architecture. FenDQ's no-code, AI-assisted approach helps teams configure quality checks quickly and adapt them as requirements change, with intelligent detection that complements your traditional rule framework.

Built for everyday users.FenDQ lets non-technical users create data-quality checks, run data through the engine, and review results in minutes. Rule-based controls and AI-assisted insights guide the process.
Build Data Quality Pipelines in Minutes
Universal connectors allow you to quickly validate data from your data feeds and databases against your business validation rules.
Drag-and-drop custom rules
Create and maintain data-quality rules with an intuitive drag-and-drop interface, including multi-step rules.
Reduce Time Spent
Be empowered by efficient workflows to view the quality of data sources and address data quality issues. Make changes to data models and rules with ease.

Low-risk Projects.We appreciate that you may not want to retire your current data management system, or may need a data quality layer between existing systems without affecting existing data pipelines.
Confidence in Change Projects
Data projects can be risky. FenDQ allows de-risking with fast proof of concept and implementation projects driven by our nimble technology, supported by hybrid detection methods that provide additional assurance over the feasibility and quality impact of proposed changes.
Works with your existing systems
FenDQ connects to your systems and databases without disrupting your existing architecture, so it can run alongside current data pipelines.
Data management and governance
FenDQ provides granular access controls, four-eye approval processes, AI insights that help identify governance gaps, automated cell-level data lineage, and audit trails to support your technology and data standards.

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