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Quest Unveils Next-Generation Data Intelligence and Modeling Solutions Demanded by AI Applications

August 2024 by Marc Jacob

Quest Software released the newest iterations of erwin Data Intelligence and erwin Data Modeler, with advanced data intelligence, quality and modeling capabilities. The powerful solutions provide a comprehensive approach to managing, governing, and leveraging data across complex enterprise landscapes, ensuring organizations are equipped to meet the challenges of AI and beyond.

A modern organization’s ability to effectively manage data goes a long way in determining its future —not only to become a leader in its industry, but to stay in the game at all. As organizations strive to harness the power of AI and advanced analytics, the importance of maintaining high-quality, reliable data has never been more critical.

The 2023 State of Data Intelligence Report highlights data quality and visibility as top challenges for enterprises. Moreover, preliminary findings from the 2024 State of Data Intelligence Report, to be released in October, indicate data quality monitoring remains a top-three data intelligence-related challenge for organizations. Without strong data quality, for example, future AI initiatives will struggle to succeed, and AI’s potential cannot be fully realized.

Quest’s new release directly addresses these challenges by cohesively managing the entire data lifecycle. The solutions integrate cross-platform data observability with advanced data quality management to provide a seamless experience for data reliability and governance across the enterprise. As a result, enterprises maintain a clear and consistent view of their data architectures, ensuring that data models are not just theoretical constructs, but are essential, living components of a dynamic, AI-ready data environment.

This release of erwin Data Intelligence 14 and erwin Data Modeler 14 offers customers a range of significant enhancements that enable them to utilize the most cutting-edge tools for data governance and control:
• AI/ML powered Data Quality and Observability – With an enhanced data quality and observability framework, erwin Data Intelligence 14, powered by AI and machine learning, continuously monitors data health across platforms. This includes advanced anomaly detection for critical data sources, ensuring that the data supporting AI models remains reliable and accurate. Self-learning capabilities further enhance its effectiveness, automatically evolving the framework to meet the changing needs of the organization and fine-tuning data quality measures based on real-world use.
• Flexible Deployment with erwin Data Intelligence Cloud - With the introduction of erwin Data Intelligence Cloud, organizations now have the flexibility to choose the deployment model that best suits their infrastructure—whether on-premises, privately hosted, or using Quest’s new cloud-hosted solution on Microsoft Azure. This flexibility allows for lower total cost of ownership and greater scalability without sacrificing any functionality.
• Streamlined Data Modeling and Governance - erwin Data Modeler 14 offers a host of new features to streamline data modeling processes, such as improved integration with modern data platforms, enhanced UI customization, and advanced reverse engineering capabilities for NoSQL platforms. These improvements make it easier for organizations to design, manage, and optimize their data architectures, ensuring data models are robust and compliant.
• Enhanced Integration and Efficiency - erwin Data Modeler 14 brings enhanced support for NoSQL databases, improved denormalization processes, and seamless integration with platforms like PostgreSQL and Google BigQuery. These updates allow for more efficient data management and ensure that diverse data environments can be easily managed and optimized.
• User-Friendly Data Quality Discovery - The new consumer-friendly data quality discovery features in erwin Data Intelligence 14 provide a search and filter experience similar to online shopping sites, enabling users to explore data quality metrics through a customizable analytics dashboard. This makes it easier for data consumers to find, analyze, and act on high-value data, enhancing data trust across the organization and accelerating decision making.


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