Embedding Ethics Into Multi-AI Agentic Self-Healing Data Pipelines
This article explores the ethical challenges of self-healing data pipelines and strategies to address them. Naveen Kolli explains how multi-agent generative AI frameworks can automate error correction while maintaining...
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Beyond Vector Databases: Integrating RAG as a First-Class Data Platform Workload
The article explores the challenges of implementing Retrieval-Augmented Generation (RAG) in enterprise environments, revealing that over 50% of deployments fail due to retrieval latency, data governance issues, and scalability...
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From Data Lakes to Intelligence Lakes: Augmenting Apache Iceberg With Generative AI Metadata on AWS
This article explores how generative AI enhances data lakes by adding semantic intelligence to metadata, transforming static storage into dynamic, searchable systems. It details an architecture combining Apache Iceberg,...
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Databricks vs. Snowflake: Complete Architecture Mapping for Enterprise AI and Big Data
This article compares Databricks and Snowflake, two leading data platforms, to help organizations choose the right tool for their needs. Databricks is ideal for AI/ML engineering and big data...
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Using Schema Registry to Manage Real-Time Data Streams in AI Pipelines
This article explores the role of schema registries in managing real-time data streams within AI pipelines, emphasizing their importance in ensuring data consistency, integrity, and scalability. The tutorial is...
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