Bryan Cafferky

As data moves into Microsoft #PowerBI, access controls from platforms like Snowflake and Databricks often break down—exposing sensitive data and creating compliance gaps. TrustLogix extends enterprise access policies into Power BI, so analysts can work with governed data across both direct queries and imported datasets. The result: consistent controls, fewer risks, and faster, trusted insights. 🔗 Learn how it works: https://hubs.li/Q03r84n40 #DSPM #DataAccessGovernance #Snowflake #Databricks

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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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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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Databricks just launched Genie Code and I'm really excited about this one!                           It's not another code completion tool, it's an autonomous AI agent that can reason through problems, plan multistep approaches, and execute full data and AI workflows end to end. The real superpower here? Unity Catalog. Having an AI coding agent that actually understands your data, the schemas, lineage, governance, business semantics, is what really separates this from other coding agents when it comes to complex data tasks. It's not just writing code in a vacuum, it knows your data. Talking with our Oil & Gas customers, I've seen firsthand how much this can seriously expedite data and ML workflows. Teams in this space are constantly stretched thin and dealing with massive, complex datasets. Having an AI partner that can actually plan and execute, not just suggest snippets, is a huge unlock.

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Snowflake credits aren’t just compute. They hide in storage too. Unused dev/test databases, stale tables, and long Time Travel or Fail-Safe settings silently drain budgets every month. Many teams never notice until credit burn rates spike. A recent Snowflake case study showed that 40% of storage in a large enterprise came from inactive data objects. That’s not innovation — that’s waste. At Anavsan, we built an AI-driven way to stop it. Our platform automatically scans your Snowflake environment, identifies idle tables, clones, and retention bloat — and helps you reclaim credits within weeks, not months. -- Pinpoint inactive storage -- Automate cleanup and governance using a secure workspace -- Reuse saved credits for new workloads Read the full blog: https://lnkd.in/eXUFNgkd Because in FinOps, every reclaimed credit fuels what really matters — growth, not waste. #FinOps #Snowflake #CloudOptimization #DataEngineering #Anavsan #CloudCostOptimization

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Claude, ChatGPT, Snowflake Intelligence, Cortex Analyst, Databricks Genie, Zenlytic, TextQL. Think about any AI agent you connect to your data. They all get questions from business users like: “What was the average number of daily active users in the last quarter?” These AI agent connects to Euno’s MCP server to retrieve metadata. That’s when Euno gives these agents the missing context they need to understand your data. ** Just a reminder that Euno is a metadata platform so we only access your metadata ** Euno runs a semantic search and looks for dashboards that use DAU (which is semantically equivalent to Daily Active Users). It filters for certified dashboards using the trust signals you’ve already set in Euno. In this example Euno finds two candidates: 1. DAU used in the User Engagement dashboards 2. DAU_NEW used in the Product Statistics dashboard Both dashboards are certified. But Euno also shows how often each has been used in the past 30 days, along with the owner or creator. With that information, the business user can confidently choose the right one and the AI agent can deliver the correct answer. The same applies to tools like Cursor. Let’s say you’re an engineer and ask: “Can you find me the Tableau dashboard for Customer Success?” Cursor will reach out to Euno’s AI assistant to get that BI context because Cursor is focused on dbt development and doesn’t have access to that layer. You can even go further and ask which dbt models power that dashboard and how those models are calculated. Euno feeds Cursor with that real-time context as you build. It’s not just for business users. It’s for developers too.

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Data silos are one of the biggest roadblocks to efficient analytics and AI workflows. MinIO’s new Aistor Table Sharing is designed to tear down those barriers by enabling direct, on-premises data access from Databricks without copying or duplicating data. Key takeaways: • Aistor Table Sharing lets Databricks query on-prem MinIO data directly, eliminating data movement. • This approach reduces complexity, storage sprawl, and latency for hybrid and on-prem use cases. • By keeping data in place while supporting modern analytics and AI consumption, organizations can accelerate time to insight. Full story: https://lnkd.in/e4mh22md #DataManagement #HybridCloud #AIAnalytics MinIO

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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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Automate. Accelerate. Analyze. Data teams spend too much time on manual coding and complex workflows. That’s why we created “WhereScape + Databricks: Automate Your Data Infrastructure and Analytics.” In this free white paper, discover how to: ✔ Cut data pipeline development from months to days ✔ Automate documentation and governance with full lineage ✔ Deploy Data Vault 2.0 on Databricks seamlessly ✔ Leverage Delta Lake, Unity Catalog, and the Medallion Architecture with automation Build smarter, not harder. Download now and transform how you deliver analytics: https://ow.ly/csY950WxoVx #Databricks #DataAutomation #DataEngineering #DataVault #Lakehouse #ETL

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Migrating to Snowflake? Don’t just move faster. Move smarter. 👇    Too many migrations copy yesterday’s complexity into tomorrow’s platform. Legacy reports. Duplicated KPIs. Unused dashboards. Technical debt — just relocated.    At BlueCloud, we’re seeing a different pattern emerge: AI-guided migrations that clean, rationalize, and modernize before scale.    Here’s what that looks like in practice:    ➡️ Rationalize your BI landscape before migration  ➡️ Align metrics and eliminate redundant logic  ➡️ Prioritize key data sources   ➡️ Build a phased roadmap tied to measurable outcomes    For executives, this means lower cost, clearer governance, faster time to value, and a foundation designed for AI from day one.    Learn more: https://lnkd.in/dGdyXx-s    #Snowflake #CloudMigration #EnterpriseAI #DataStrategy #ModernData 

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