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Combining Data Mesh and Data Fabric

Data silos represent a major business challenge, as noted by 60.9% of organizations in a recent Trends in Data Management survey. Without shared information, companies risk duplication, poor data quality, and missed opportunities for innovation. Consequently, many companies turn to modern and integrated data architectures. When doing so, organizations often consider two main approaches: data mesh and data fabric. Data […]

IBM Demo: How Data Lineage Enables Simpler Regulatory Compliance, Data Governance and Technical Impact Analysis

Download the slides here>> A dive into how IBM’s Manta Data Lineage solves complex problems in regard to meeting compliance standards for various industries across a wide range of technologies, and further explore how Data Lineage can streamline data governance and technical impact analysis. We hope to see you at the next DATAVERSITY Demo Day […]

Data Synchronization: Definition, Tips, Myths, and Best Practices

Businesses rely on accurate, synchronized information to make informed decisions. Because discordant data leads to operational inefficiencies, missed opportunities, and costly mistakes. Hence, a unified, reliable source of truth is key, which is possible through data synchronization. It helps maintain consistency across disparate systems, enhancing data reliability and improving decision-making. So, to get started with […]

RAG (Retrieval Augmented Generation) Architecture for Data Quality Assessment

A large language model (LLM) is a type of artificial intelligence (AI) solution that can recognize and generate new content or text from existing content. It is estimated that by 2025, 50% of digital work will be automated through these LLM models. At their core, LLMs are trained on large amounts of content and data, and the architecture […]