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Explore why AI complements rather than replaces BI practices in analytics workflows, with insights on effectively integrating natural language interfaces alongside traditional dashboards.
Explore the unintended consequences of the Analytics Development Lifecycle, including stakeholder marginalization and bottlenecks, and discover solutions for restoring data access while maintaining governance standards.
Explore the misconception that data governance equals governing data. Oriol Mirosa shares scalable practices for structuring and extracting value from data, bridging the gap between data producers and consumers in organizations of all sizes.
Discover effective strategies for embedding data teams within business units to bridge the AI implementation gap, creating virtuous cycles where data professionals gain domain expertise while business teams improve data literacy.
Discover practical frameworks for AI implementation assessment, learning when to choose AI versus simpler methods. Gain data-driven perspectives on building quality foundations and governance before pursuing AI solutions.
Discover how AI's unpredictable workloads will disrupt traditional data platforms, requiring new approaches to handle chaotic query patterns, tighter latency constraints, and evolving optimization strategies.
Discover TapeAgents, a framework for AI agent development featuring "tape" recording capabilities that capture agent actions, thoughts, and observations, enabling unprecedented transparency and data-driven optimization for robust real-world applications.
Discover how e6data's lakehouse compute engine delivers 10x faster SQL analytics at lower costs through K8s native architecture and object-store-native approaches for sub-second latencies under heavy concurrency.
Discover how enterprises like Canal+ and NASA scale Generative AI through Zerve's distributed computing engine, transforming experimental AI into cost-efficient business solutions while streamlining development and reducing infrastructure costs.
Discover strategies for structuring data teams across different organizational models, with insights on how reporting relationships shape priorities, influence, and success metrics in today's AI-driven landscape.
Explore how enterprises can guarantee event data quality upstream through Data Mesh principles, with insights from Avo's platform and real-world examples from companies like Moody's, Fender, and IKEA.
Discover why powerful foundation models don't guarantee successful AI products. Explore the engineering, UX, and business considerations that bridge the gap between model capabilities and solving real user problems.
Discover Tower's elegant 2-layer data stack where compute engines coexist harmoniously, running Python frameworks from ETL to inference on scalable single-node compute with Iceberg open storage.
Discover how TopK's unified search platform simplifies the modern search stack into a single API, combining vector databases with production-ready search solutions that integrate dense/sparse vector, text, and faceted retrieval with custom scoring.
Discover NAO, an AI code editor built for data teams that unifies fragmented analytics engineering workflows across multiple tools, reducing context switching and enhancing productivity for data professionals.
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