AI - Data Virtuality

Platform for managing & optimizing data sources with intelligent caching, securing access, and complying with certifications and encryption standards.

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About Data Virtuality

Data Virtuality is a leading data technology company that empowers businesses to unlock the full potential of their data by providing a unified platform for connecting and managing all data sources. With over 200 instant connectors, Data Virtuality enables businesses to query multiple data sources as if they were a single database, accelerating large data processing through intelligent caching and materialization techniques. Their platform includes AI-based data structure optimizations that create a semantic data layer for quick adaptation to changing business requirements.

Data Virtuality offers flexible deployment options, including Software as a Service (SaaS), Self-Hosted Cloud, and On-Premise solutions, ensuring secure and compliant access for modern businesses. Their platform boasts numerous certifications, such as ISO 27001, SOC 2 Type 2, and SOC 3, along with GDPR and HIPAA compliance. Additionally, they offer extensive support for authentication protocols, security protocols, and encryption standards.

Data Virtuality's solutions provide several benefits, including enabling subject matter experts to access data self-service, reducing reliance on data professionals for routine queries. The platform includes a Business Data Shop with a user-friendly interface for easy data access and an extensive metadata catalog for enhanced data discovery.

Furthermore, Data Virtuality's platform offers centralized controls and audit capabilities, ensuring high data quality, security, and compliance. Users can manage access with a robust permission system, secure sensitive data with column masking and fine-tune access at row and column levels for privacy and compliance. The platform also keeps a detailed history of metadata changes for effective tracking and reverting, ensuring data integrity.

Data Virtuality's customers come from various industries, including financial services and banking, where they have successfully implemented use cases such as data governance, data quality checks, self-service BI, data preparation for regulatory reporting, digital marketing analysis, and the refinement of business logic implementation.

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