In-depth articles discussing principles, practices, use cases, guides, and models that cover everything from Data Governance policies to Data Mesh architectures
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Discover the importance of a semantic layer in data catalogs and how it enhances data discoverability and usability in your data platform.
Learn how to build AI agents that provide conversational data analytics for enterprises, focusing on architecture, deployment, and LLM selection.
Explore how Anthropic's MCP and Google's A2A protocols are transforming AI interoperability, enabling seamless integration and collaboration.
Learn the critical role of training in successful FinOps adoption, fostering collaboration, enhancing cost-efficiency, and maximizing cloud ROI.
Explore critical aspects of data privacy in data architecture, including compliance, data deletion strategies, consent management, and secure test...
Explore strategies for integrating metadata into data catalogs, analyzing pull and push approaches, their advantages, and setbacks.
Discover how MLOps can streamline and scale your machine learning workflows, improve collaboration, and ensure compliance in AI initiatives.
Discover how platform engineering enhances software development by integrating technologies, standardizing workflows, and focusing on user-centric...
Discover 6 immediately implementable LLM optimization techniques to enhance AI performance, reduce resource consumption, and improve inference...
Discover how the Model Context Protocol (MCP) standardizes interactions, enhancing interoperability and automation within enterprise systems.
Navigating data privacy with large language models: Learn about risks and challenges for secure and compliant implementation in the age of AI.
Explore the distinctions between AI agents and tools, their real-world applications, and their future implications for businesses and technology.