Serge Rielau

Agents don’t have an intelligence problem. They have a context problem. They fail because their context layer is scattered, stale, slow, or hard to use. Introducing Redis Iris, the new context and memory solution that turns fragmented enterprise data into live, agent-ready context. Redis Iris is a context engine, an important layer in an AI stack that sits between an agent and the data it needs to act, feeding the right context, in the right form, at the right time. https://redis.io/iris/ https://lnkd.in/gfEJHtnr

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Just published: "The Silent Drop: My Journey with Snowflake OpenFlow CDC Pipelines" 🚀 If you've ever stared at a green NiFi processor that refuses to output a single FlowFile, this one is for you. I walk through the specific "gotchas" of setting up CDC in a Bring-Your-Own-Cloud (BYOC) environment—from handling "Zombie" Postgres connections to fixing silent schema issues. Read the full story here: 

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Fusion-to-data warehouse integrations are hard. APIs break. Custom code fails. Manual exports never end. Orbit Analytics simplifies the journey with automated, Oracle-native Data Pipelines. Instant replication to your warehouse of choice (Snowflake, Oracle DW, Azure Synapse). No fragile integrations. Built-in data quality. Governance throughout. Move your Fusion data reliably and at scale.https://hubs.ly/Q03_qKHT0 #orbitanalytics #oraclefusioncloud #datapipelines

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Still running Snowflake schema changes with manual SQL scripts and ticket handoffs? That approach leads to drift, delays, and deployment headaches as your data warehouse grows. The Liquibase + Snowflake Cheat Sheet gives you a quick-start guide to CI/CD discipline for schema changes, including versioning, rollback, policy checks, and audit trails. Grab your copy: https://hubs.li/Q0461NLW0 #Snowflake #DatabaseDevOps #Liquibase #DataEngineering #DevOps

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Good Morning LinkedIn BigDataDave Blog article on using Modulo Division in a Join for creating, distributing, and joining fake data from Snowflake's sample data! https://lnkd.in/gx2jHGVv

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Great news, Snowflake Cortex Agents API is now GA! Developers can now build trusted, production-ready data agents that orchestrate insights across structured and unstructured data using Cortex Search and Cortex Analyst. Build context-rich agents today: https://lnkd.in/d7GNsEwj

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The Databricks Startups team answers founders’ most common AI questions—where to start without hype, how to stay compliant with sensitive data, what to build versus buy, how to cut hallucinations, and how to keep costs in check. 💡 Get step‑by‑step starting points, governance patterns for sensitive data, a pragmatic build‑versus‑buy lens, tactics to curb hallucinations, and cost controls that scale. 🔗 Full post: https://lnkd.in/ehRa3Yp5 #Databricks #DatabricksForStartups #AI #GenAI #MLOps

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Snowflake just released Iceberg V3 support into public preview today. A few highlights. Nanosecond timestamp precision – Iceberg tables can now match the same precision as native Snowflake tables. Row lineage metadata – better visibility into how individual rows evolve across updates and deletes. VARIANT support – yay 🙂 Deletion vectors – enabled by default in V3. Improves performance from reducing the overhead of managing many delete files. Can mean faster ingestion and transformation! Nice to see Iceberg tables continuing to close the gap with native tables in Snowflake.

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After taking the market by storm, there's now a clear pattern that has developed with companies abandoning Snowflake and migrating to Google Cloud's BigQuery. This is a great breakdown by Zencore's ☁️Jay Jay Sisti☁️ on why BQ is clearly a better option for many organizations. David W. Graham Polley #zencore #googlecloud #googlecloudpartner

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Why compute relationships when you can store them? That’s the core of graph thinking. Michael Hunger, VP of Product Innovation at Neo4j, breaks down how their platform treats connections as data and how that changes what’s possible for supply chain, security, and more. Tune in to his full conversation with Simon Maple.

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Today we are launching DSC Optimizer. We built this product after years of working inside Snowflake environments where the same pattern kept showing up: warehouses sized once and never revisited, auto suspend settings left at defaults, and credits burning quietly in the background. Optimizer connects with read only metadata access and analyzes how your warehouses are actually performing. It shows where capacity is oversized, where settings should change, and what those adjustments mean in real dollar savings. Setup takes about 20 minutes. No disruption to workloads. No risky permissions. This is the tool I wish every team had before their Snowflake bill crept up month after month. If you are running Snowflake and have not reviewed warehouse performance recently, there is likely savings available. Happy to walk through it with anyone interested.

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Streaming pipelines don’t give you the luxury of batch-style cleanup. So most teams end up pushing all events as they are, be it malformed JSON, missing fields, or unexpected data types. These bad or low-quality events are then “fixed” with downstream queries or jobs. But this approach takes its toll on the warehouse: → Query complexity grows → Datasets become inconsistent → Transformations start breaking → Data quality checks throw errors On top of it all, the offending events are very hard to trace. Unless you deal with them within the pipeline, not after the fact. GlassFlow helps teams address data quality in the streaming layer: ✅ Invalid events are filtered before they reach the warehouse ✅ GlassFlow isolates them in a Dead-Letter-Queue ✅ You can replay the failed events any time All of this without stopping the pipeline: valid data continues to flow uninterrupted. Forget crashes, crowded datasets, and long debugging sessions. GlassFlow catches problematic events mid-flight, so you can deal with them before ingestion.

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In this world of Agents.. how do you ensure that your agent is doing what it's designed to do? Agent Evaluation is one of the core capabilities required for Explainable AI. @Snowflake #Cortex #Agents Evaluation is now GA.

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I’ve been testing both approaches, and the difference is pretty clear. Some tools still stop at “here’s how to do it” while Cortex Code actually builds and delivers the outcome. That shift from guidance to execution is what really stands out.

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Demo Class Overview In this demo class, I will cover the following: ✅ Course Content Overview An overview of 24+ hands-on notebooks designed to help you understand, explore, and practice every major Snowflake Cortex feature. ✅ Certification Preparation A walkthrough of how these notebooks are structured to directly support your preparation for the Snowflake Generative AI certification, with practical hands-on experience, real-world use cases, and coverage of exam-relevant concepts.

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Snowflake's authentication deprecation is moving fast. Are Phase 1 is done — human users are on MFA. But Phase 2 starts in weeks, and Phase 3 lands August–October with a date Snowflake assigns, not one you choose. Most teams will treat this as a credential rotation exercise. BUT it's actually a governance opportunity you won't get again for a long time. When you rotate credentials on a shared service account, you're implicitly endorsing everything that account can access. The migration forces you to touch every service account anyway, and the incremental cost of getting the role structure right at the same time is low. Doing it later, as a separate project, is much higher. Migrate and narrow simultaneously. Full breakdown linked in comments. #snowflake #dataengineering #datagovernance #clouddata

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Private Preview - Databricks One on Azure Simplifies AI and Data Development. What if you could manage data engineering, analytics, and AI development on one platform? Databricks One in Azure Databricks is creating waves. It merges advanced tools for data science and AI with simplified workflows and enterprise-grade governance. Now, you can focus on innovation instead of juggling tools. Check out what it offers: 💡 Unified workflows to align data teams seamlessly 🔒 Top-tier governance for improved compliance and security ⚡ High-performance capabilities to meet enterprise demands 🤝 Collaborative tools to drive teamwork and accelerate insights This is more than a platform; it's a shift in data strategy. Simplification without compromise. Businesses leveraging integrated platforms like these often see faster deployment times and reduced operational burdens. Are you prepared to streamline your data approach? Explore its potential today: https://lnkd.in/d--dK6Vr

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