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Data Infrastructure & Architecture: Building the Foundation for Analytics and AI
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Data Infrastructure & Architecture
Building Scalable Foundations for Data and AI
The technical foundation enabling data collection, storage, integration, and access. Covers data warehouses, data lakes, lakehouses, data mesh architectures, pipelines, knowledge graphs, vector databases, and integration patterns. Maturity evolves from siloed systems to unified, scalable platforms that support analytics and AI workloads.
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Building Your First Data Platform: A Practical Starting Point
Actionable guidance for organizations building their first modern data infrastructure. Covers essential vs. optional components, managed vs. self-hosted tradeoffs, quick-win architectures that create immediate value, and evolution paths that don't require rebuilding from scratch as needs grow.
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When Milliseconds Matter (And When They Don't): The Real Economics of Streaming Data
Examines use cases where real-time data processing creates differentiated value and the architectural patterns that enable it. Covers streaming platforms, event-driven design, operational analytics databases, the organizational changes needed to act on real-time insights, and cost-benefit analysis for streaming adoption.
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