How Snowflake Cortex Revolutionizes Data Analytics with AI

✨ Data is the new oil — but only if you can refine it. ✨ 🚀 Databricks just hit a $𝟏𝟎𝟎𝐁+ valuation — proof that investors believe AI-driven data analytics will power the next decade of business transformation. 🔹 Why Databricks matters: ✅ Unified platform for data, ML & BI ✅ Handles structured + unstructured data at scale ✅ Real-time insights, not just historical reporting ✅ Collaboration across analysts, engineers & data scientists 🔑 For Consulting firms & Business leaders, this isn’t just hype — it’s a competitive advantage: • Productivity gains in analytics = faster, sharper decisions • AI + Data platforms shift businesses from ~ 𝐖𝐡𝐚𝐭 𝐡𝐚𝐩𝐩𝐞𝐧𝐞𝐝 ⟶ 𝐖𝐡𝐚𝐭’𝐬 𝐧𝐞𝐱𝐭 • Consulting partners using Databricks are already delivering AI at scale 💡 Lesson: Businesses that invest in data + AI together will lead the future. 👉 What’s your bet — specialized tools like Databricks or end-to-end ecosystems like Google Cloud /Azure Cloud? #Databricks #AI #DataAnalytics #BusinessIntelligence #Consulting

🚀 Why so much AI/ML potential goes uncaptured Did you know Data Scientists spend 60–80% of their time just preparing data? That means less time building and deploying the models that actually solve business problems. On top of that, over 60% of organizations struggle to move models into production because of siloed data, compute bottlenecks 🚱 , and the lack of a unified platform ❌ . This is where Snowflake comes in: ✅ One secure platform for all data types (structured + unstructured) ✅ Seamless collaboration between Data Science, IT, and Ops teams ✅ Elastic, intelligent infrastructure with no manual tuning ✅ Faster path from experimentation → production At Oktana, we pair our nearshore engineering teams with Snowflake’s data power to helps companies: - Build scalable AI/ML use cases. - Modernize data storage & migration pipelines. - Integrate cloud, full-stack, and analytics platforms end-to-end. 💡 The result: Data scientists focus on what they do best — solving problems — while we handle the heavy lifting of integration, development, and scaling. 👉 If your team is exploring how to unlock the real value of AI with Snowflake or other data platforms, we’d love to share use cases we’ve delivered across industries. #Snowflake #AI #MachineLearning #DataEngineering #Nearshore #BoughtCapacity

💡 The future of analytics belongs to pipelines that think and repair themselves! 🔥 By combining Microsoft Fabric and Azure AI, we embed intelligent agents that monitor, detect, and self-heal turning static pipelines into adaptive systems. The result is enterprise analytics that stay reliable, governed, and cost-efficient, even as data volumes grow 📈 ✅ Executives gain confidence that dashboards refresh on time. Analysts focus on insights, not troubleshooting. Operations scale without adding burden 👀 👌 This is Agentic Analytics where pipelines that run and optimize themselves. It’s not a concept for tomorrow; we’re delivering it today 👉 Read how we build self-healing data pipelines with Fabric + Azure AI https://lnkd.in/gEt5CyYB #AgenticAnalytics #MicrosoftFabric #AzureAI #EnterpriseData #IntelligentAutomation #FutureOfAnalytics #ZCS

While cleaning over the weekend, I stumbled on something very special — my signed copy of Ralph Kimball’s Data Warehouse ETL Toolkit. 📘 The note inside reads: “Vamsi, keep to the grain – Ralph Kimball”. A reminder that while technologies change, the fundamentals of data warehousing remain timeless — and that organized, governed data delivers value that is insatiable. One of the highlights of my career was meeting Ralph Kimball himself — a moment that shaped how I think about data. Many might see data warehousing as a “lost art,” but I insist it is still the foundation of modern data and AI. Even in today’s age of cloud and unstructured data, trusted, structured, well-modeled information is what makes advanced analytics and machine learning possible. Without that base, innovation cannot stand. The fundamentals don’t go out of style — they evolve with us and continue to guide the future. 🚀 #DataWarehousing #RalphKimball #AI #DataStrategy #Analytics #DataArchitecture #DataInnovation #Cloud

Today marks a crucial juncture in the AI + Data Intelligence realm. Recent advancements are not solely transforming infrastructure but also reshaping how businesses approach growth, scalability, and competitive edges. In the realm of AI infrastructure, Nebius has clinched a monumental $17–19B AI cloud computing deal with Microsoft, bolstered by Nvidia-backed data centers in New Jersey. This underscores the increasing significance of data-centric operations in enterprise AI. On the frontlines, data and AI enterprises are forging ahead. Databricks now anticipates an annualized revenue run rate of $4B, with a substantial $1B stemming from AI offerings alone. This underscores the pivot towards unified data and AI platforms as pivotal to business strategies. In a nuanced landscape, the momentum in AI encounters a twist. A U.S. Census Bureau survey reveals a slight decline in AI adoption among major corporations, from 13.5% to approximately 12%, prompting reflections on sustainability and return on investment. Google Cloud's CEO disclosed a robust 32% year-over-year revenue surge ($13.6B in Q2), propelled by tailored AI chips and Gemini models. This accentuates the significance of vertical integration and specialized tools in a competitive cloud market. These dynamics paint a multifaceted narrative: while capital influx and innovation elevate the data-AI fusion, corporate tech integration faces heightened scrutiny and adjustments. The implications for you are clear: whether constructing data pipelines, crafting AI workflows, or designing BI dashboards, the path ahead is evident: - Ensure Scalability by preparing your data architecture (e.g., lakehouse models) for AI-driven workloads. - Emphasize Strategic ROI by prioritizing initiatives that yield tangible results, not just buzz. - Harness Toolchain unity by leveraging integrated platforms (cloud + AI + custom silicon) for distinctiveness. - Serve as an Adoption navigator by guiding enterprises through adoption challenges with practical, measurable use cases. In today's business analysis domain, AI devoid of intelligent data fusion amounts. #AI #DataIntelligence #BusinessAnalysis #DataPipelines #AIWorkflows #CloudAI #BI #TechLeadership

💡 Data Chaos or Data Clarity? The AI Difference Today, businesses generate more data in a single day than they did in entire years just a decade ago. But here’s the challenge: 📉 70% of that data often goes unused. 📉 Decision-makers spend more time reconciling spreadsheets than acting on insights. Now, imagine turning that data chaos into clarity: ✅ Unified data platforms (Databricks, Snowflake, Azure, AWS, GCP) that centralize and clean your data. ✅ AI-powered agents that not only analyze but also recommend and act. ✅ Real-time insights that cut through noise and guide smarter, faster decisions. The result? Businesses that embrace Data + AI are not just optimizing operations—they’re rethinking how they compete, serve customers, and grow. 👉 In my role, I work with organizations to move from data overwhelm to data-driven confidence—helping them unlock real business impact with modern platforms and AI solutions. If you’re exploring how to transform your data challenges into opportunities, let’s connect and exchange ideas. #Data #AI #DigitalTransformation #BusinessGrowth #Innovation #EITB

Databricks has introduced Databricks One, a new simplified interface built for business users. Instead of navigating clusters, notebooks, or SQL queries, people can now explore data, track KPIs, and ask questions in plain language with AI/BI Genie. It also brings apps that combine analytics, AI, and workflows, plus a personalized “For you” section that highlights what’s most relevant. The best part is that even users with limited access rights can use Databricks One without needing the full workspace. I t’s currently in public preview and can be enabled by admins in the Previews section of Azure Databricks. More info & also where Demo below comes from: https://lnkd.in/e26Yt8kk #dataai #databricks #advisory

📢 From a CDO to another CDO: Why Databricks Matters! Too often, data platforms are seen as technical decisions. But as CDOs, we know the reality is different. It’s about: 🚀 Balancing innovation with governance 💰 Delivering business value while managing cost 🌍 Future-proofing for AI while fixing legacy silos And here’s the challenge: in most organisations, data is everywhere, but trust and value are missing. Pipelines are fragile. Shadow data grows outside governance. Costs raises while business confidence shrinks. That’s where Databricks changes the game. It’s not “just another tool.” It’s a unified platform for data + AI that addresses the problems that keep CDOs up at night: ✔️ One place for structured, unstructured, and streaming data ✔️ Governance by design with Unity Catalog ✔️ Elastic scale, from BI dashboards to Generative AI ✔️ Open and interoperable (no lock-in) Why this matters at leadership level: 📊 Business confidence in governed, real-time insights ⚡ Speed to value with faster delivery and quicker ROI 🛡️ Risk reduction through compliance, lineage, and auditability 🌍 A foundation for AI, ML, and the next wave of innovation And the impact is real: For a health organisation, we migrated from Azure to AWS with zero data loss, while introducing Unity Catalog for stronger governance. At a gaming company, we delivered sensitive data migration and ML modernisation to meet regulatory compliance across regions. In public sector housing, we replaced fragmented reporting with a unified analytics platform. Each case = fewer silos, stronger governance, and faster insights. From one CDO to another: Databricks isn’t just a technology choice! It’s a strategic enabler for how you govern, deliver, and innovate with data. 👉 If you’re ready to start the discussion on what this could look like in your organisation, I’d be happy to have that conversation with you directly! #Databricks #Unifeye #DataPlatform #Leadership #Governance #BusinessValue #FutureReady #AI

Recently, I had the opportunity to implement Snowflake Cortex Analyst for one of our customer, empowering them with an advanced conversational analytics solution! By leveraging Snowflake’s Cortex Analyst, have enabled business users to ask data questions in natural language—and receive instant, accurate insights—without needing to write SQL statements. The implementation seamlessly bridged the gap between non-technical teams and complex data, accelerating decision-making and enhancing business intelligence across the board. In my new Medium blog, I detail our approach, the technical architecture, and best practices that helped us deliver a self-service analytics experience—powered by secure, state-of-the-art LLMs from Meta and Mistral—right within the Snowflake Data Cloud. https://lnkd.in/gAEZJPFq #Snowflake #Snowflake #CortexAnalyst #ConversationalAnalytics #DataCloud #learn #Genpact #semantic #CortexAI