Quantexa launches AI tool Unify for Microsoft Fabric
Quantexa has announced the launch of its AI-powered workload, Quantexa Unify, for Microsoft Fabric, aimed at transforming data quality and usability across enterprises.
Quantexa Unify is designed to provide users with advanced entity resolution capabilities to perform high accuracy data-matching and relationship discovery at scale. This tool is expected to enhance organisations' data quality, eliminate silos, and lower operational costs, thus addressing prevalent data readiness challenges for AI and facilitating more informed decision-making.
Chief Product Officer Dan Higgins commented, "Announcing the preview of Quantexa Unify for Microsoft Fabric at Ignite is a significant milestone in our ongoing collaboration with Microsoft. Our AI-powered workload for Microsoft Fabric will transform how organisations achieve data readiness to maximise their generative AI investments. This powerful integration helps organisations create the foundation for augmented decision-making by resolving complex entity relationships using external and internal data sources with speed and precision. By tapping into the scalability and flexibility of Microsoft Fabric, we are empowering businesses to drive innovation and harness the full potential of their data like never before."
The Quantexa Unify workload is integrated with Microsoft Fabric to allow data engineers, scientists, analysts, and business users to continuously integrate and update data from multiple sources. The workload features no-code, automated data mapping, advanced entity matching, and contextualised insights, all designed to enhance the usability and reliability of an organisation's data estate.
As part of its data processing, Quantexa Unify reads data from OneLake, automates data cleansing and normalisation, and executes comprehensive data matching procedures. This creates a unified, interconnected view of the data, supporting Microsoft Power BI reports to illustrate data quality metrics and issues.
Amir Netz, Technical Fellow and CTO for Microsoft Fabric, expressed enthusiasm for the collaboration stating, "We are pleased to see Quantexa's innovation bring such a compelling capability to Microsoft Fabric. This enables organisations to use their data within Microsoft Fabric to foster better decision-making and enhanced operational efficiency. As customers increasingly rely on Microsoft Fabric to accelerate their digital transformation, this capability will allow them to gain deeper insights they expect from their data investments, all within a trusted enterprise-wide data estate. We look forward to continuing to collaborate with Quantexa to help our customers unlock new opportunities and drive confidence in their AI and data-driven initiatives."
In addition to the public preview, Quantexa has launched a private preview targeting customers ready to deploy Quantexa Unify. Novo Banco, a prominent financial institution in Portugal, is among the early participants. Chief Operating Officer Seamus Murphy from Novo Banco shared, "Understanding customer behaviour through a comprehensive data view lets banks personalise communications and services, fostering stronger client relationships, and simultaneously protecting them and the bank with a single investment.
The current trend of creating vertical solutions is not cost effective and does not create the intended business impact. An enterprise-wide data estate is the future of effective data operationalization in banking. Quantexa's Unify for Microsoft Fabric will be the foundation for us to dismantle organisational and data silos, enabling advanced analytics, efficiency using AI, and better customer service."
Quantexa's new solution aims to provide an effective data foundation for existing analytical tools, ensuring data is consistently refreshed and reliable for business intelligence and operational purposes. This integration into Microsoft Fabric is intended to offer significant improvements, including enhanced scalability, performance, and democratized data access, supporting faster and more accurate decision-making processes across enterprises.