Will Davis

We've launched the dbt_semantic_view package, seamlessly integrating the Snowflake semantic view with dbt's disciplined workflow. This means you can now: - Centralize Metrics: Define key metric logic (FACTS, DIMENSIONS, METRICS) natively in Snowflake's semantic view for a single source of truth. - Enable CI/CD: Apply dbt's strengths (declarative YAML, testing, and version control) directly to your semantic layer definitions. - Ensure Governance: Automatically manage privileges and validate relationships to ensure every consumer, from BI tools to AI agents, uses trusted data. - Unify your governance framework and ensure consistent, high-performance metrics across your enterprise. Learn more and get started: https://lnkd.in/eZqiwT-g

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We’re excited to announce Anthropic’s Claude Haiku 4.5 is now available for customers on Snowflake Cortex AI to use natively within the Snowflake secure perimeter. With its near-frontier performance and lightning-fast speed, it’s great for enterprise use cases: ❄️ AI-powered pipelines – Build high-volume, multimodal analytics pipelines directly in Cortex using AISQL. Claude Haiku 4.5 delivers Sonnet 4 level performance at lower cost and faster speeds which is ideal for scaling data processing workloads. 👉 https://lnkd.in/gEZm-KK7 ❄️ Agentic Systems – Power low-latency, cost-efficient agents that reason, act, and adapt in real time—built for enterprise scale and secured within Snowflake’s trusted, governed environment. 👉 https://lnkd.in/gzbNXN_T ❄️ Actionable Insights – Coming soon in Snowflake Intelligence, to give business users more precise, state-of-the-art insights from structured and unstructured data, particularly in finance and research. 👉 https://ai.snowflake.com/

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As the #AI revolution reshapes enterprise tech, SAP & Oracle are taking diverging strategies. On SAP's recent earnings call, CEO Christian Klein doubled down on his commitment to data + AI + #agents, not infrastructure. Tune in to Cloud Wars Minute for more → https://lnkd.in/epcdn8je

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The Neo4j + Snowflake integration is now generally available! At #SnowflakeSummit2025, Matt Cannon joined The Ravit Show with Ravit Jain to unpack what this launch means for enterprise teams: ✅ No data movement ✅ No overhead ✅ Graph where your data lives From financial services to cybersecurity, demand is for graph growing fast, and this is just the beginning. Watch the full interview: https://lnkd.in/d36t-d2Y #Neo4j #Snowflake #GraphDatabase #GraphAnalytics #GenAI

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Y'all heard about DeepSeek R1! But, did you know that Denodo supports #DeepseekR1 for Query RAG, offering a solution that ensures #AI applications access real-time #data without the burden of heavy data replication. How? Read this blog to explore how the #DenodoPlatform enhances query generation, outperforms traditional #DataIntegration methods, and how real-world customers are leveraging this powerful combination to transform their #GenAI initiatives 👉 https://okt.to/r4fI0O #LLM #AIAdoption

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We’re teaming up with Snowflake to bring the power of Cortex AI to the Moveworks AI Agent Marketplace. ❄️ ⏩ Soon, teams across your org can:  🔎  Query data in natural language 🧐 Analyze data instantly without toggling between tools ⚡ Move from insight to action, faster than ever Joint customers can install the Snowflake Cortex AI Agent directly into their AI Assistant. 𝗗𝗶𝘀𝗰𝗼𝘃𝗲𝗿 𝘄𝗵𝗮𝘁’𝘀 𝗽𝗼𝘀𝘀𝗶𝗯𝗹𝗲 ➡️ https://lnkd.in/gAvTxTht #AgenticAI #AIAgentMarketplace

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We’ve introduced a new Semantic Modeling Language (SML) that’s changes how we see teams defining and managing analytics logic across their businesses. SML lets you create reusable, versionable semantic objects: like metrics, dimensions, and hierarchies - that can be shared across tools and teams. Instead of duplicating logic in every BI tool or pipeline, you define it once and apply it consistently. This allows you to add structure and consistency where it matters. Analysts can move faster with pre-defined models. Engineers can version and test models like code. And everyone aligns around a common data language. We’re also publishing a public GitHub repo with semantic models for platforms like Salesforce and Workday, plus converters for dbt, Power BI, and soon Looker. That makes it easier to go from raw data to answers. SML is designed to support collaboration, enforce consistency, and scale with the complexity of modern analytics environments.

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In this joint conversation, Ververica’s Field CTO and Steadforce’s CTO dive into how #ApacheFlink 🐿️ is transforming the industrial world, from predictive maintenance and anomaly detection to adaptive production control. 🎯 Learn how: 🔧 Manufacturers extend IT/OT architectures with Flink ⚡ Streaming boosts supply chain agility 👥 Teams adopt “evolution over revolution” for long-term success Whether you’re in manufacturing, logistics, or infrastructure, this is your playbook for deploying scalable, secure, and maintainable streaming solutions. 💥https://hubs.li/Q03ngHYc0 #RealTimeData #Steadforce #IoT #StreamingAnalytics

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Real-time streaming just got a serious upgrade. Firebolt × Confluent means teams can now stream data directly into Firebolt and power dashboards, apps, and AI pipelines instantly - without the data engineering overhead. 👉 Read more about what this unlocks for modern data teams: https://okt.to/gKoiyD #DataEngineering #AI #StreamingData #Firebolt

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💡 Today’s most innovative organizations are no longer asking if relationships in data matter — they’re asking how fast they can uncover them. We’re thrilled to announce 𝐍𝐞𝐨4𝐣 𝐆𝐫𝐚𝐩𝐡 𝐀𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬 𝐟𝐨𝐫 𝐒𝐧𝐨𝐰𝐟𝐥𝐚𝐤𝐞 – a native Snowflake application. This brings Neo4j’s advanced graph algorithms — the same ones used by leading banks, telcos, and healthcare systems — directly to where your data lives. No ETL. No complexity. Just the ability to uncover connected insights using 𝐣𝐮𝐬𝐭 𝐒𝐐𝐋, within the scale, security, and governance of your Snowflake environment. With this integration, we’re helping enterprise leaders: 🔎 Detect fraud and risk faster 📈 Drive AI model precision 🚀 Accelerate time to value on strategic data initiatives 💰 Cut analytics costs by up to 70% The power of graphs, the simplicity of Snowflake — now working together to turn your data cloud into a true insight engine. 👉 Learn more: https://lnkd.in/gbMuU8Si Sudhir Hasbe Anurag Tandon John Coulston Chandra Rangan Pagely Tucker Robin Kim Virginia Barasch Matt Connon Tanuj Bansal Nathan Barney #Neo4j #Snowflake #AIDataCloud #GraphAnalytics #LLM #ConnectedEnterprise #ExecutiveInsights #KnowledgeGraph #EnterpriseAI https://lnkd.in/gxVCbpWN

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One of the most promising applications in the #HCM industry is the future use and implementation of AI agents. But what are they, how can we best leverage them, and how do we bring our teams along on the journey with us? https://ukg.inc/4jS0SUj

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For FileMaker developers, AI has often felt either overhyped or irrelevant to real solutions. Claris MCP changes that, not by adding “AI features,” but by exposing what FileMaker already does well in a way AI tools can safely and predictably use. This article walks through what MCP actually enables today for FileMaker developers, especially beyond the familiar “chat over your data” examples. The focus is on practical outcomes: calling FileMaker scripts, automating workflows, governing access, and using AI as an orchestrator of business logic rather than a replacement for it. If you’ve been curious about MCP but unsure where it fits, or skeptical that AI could be useful in real FileMaker solutions, this is written with you in mind.

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