Snowflake's growth, valuation, and execution risks in AI and data market.

🚀 From Dashboards to Decision Intelligence: The Shift We Can’t Ignore For years, “being data-driven” meant building dashboards and tracking KPIs. But at scale, dashboards alone don’t create impact — decisions do. The real transformation happens when Data Engineering + BI + AI + Cloud come together to deliver Decision Intelligence: ✅ Data pipelines that handle millions of records daily with near real-time accuracy. ✅ BI dashboards that explain why metrics changed, not just what happened. ✅ AI models that simulate scenarios and recommend the next best action. ✅ Cloud-native systems (AWS, Snowflake, GCP) that scale seamlessly. In my work developing data pipelines, ETL workflows, and 50+ executive dashboards, I’ve seen one truth: 👉 Companies that win aren’t the ones with the most dashboards — they’re the ones where insights instantly translate into action. The future of analytics isn’t reporting the past. It’s about guiding the next move — intelligently, automatically, and at scale. ⚡ What do you think — would you trust an AI-powered BI system to recommend your next business decision? #DecisionIntelligence #DataAnalytics #BusinessIntelligence #AI #Cloud #DataEngineering

Snowflake’s 14% surge highlights a clear market tension: enterprises urgently need scalable data infrastructure to operationalize AI (problem); Snowflake’s multi‑cloud data platform and raised revenue guidance offer a credible path to capture that spending (solution). Key takeaways follow. Macro trends - AI adoption is driving outsized capex on data stores, orchestration and model-serving infrastructure. Nvidia’s upbeat guide and Databricks’ >$100bn valuation reflect broad demand for AI‑native platforms. - Cloud migration and multi‑cloud strategies increase addressable market for neutral data‑platform vendors. Key factors - Snowflake raised FY product revenue to $4.40bn, outperforming expectations and triggering analyst upgrades. - Its multi‑cloud architecture and focus on simplifying AI workflows are strong competitive advantages. - Market reaction is amplified by sector sentiment; Snowflake is now trading at ~142x forward earnings, well above peers. Risks - Elevated valuation implies high execution expectations; any growth miss will be punished. - Intensifying competition (Databricks, cloud providers, specialist databases) and customer consolidation risk margin pressure. - Macro slowdowns or reduced enterprise IT spend would hurt demand. Actionable insights - Investors: prefer staged exposure—scale into positions on proof points (ARR, net‑retention, gross margins) rather than momentum alone. - Portfolio managers: consider thematic baskets (data + AI infra) to diversify single‑name risk. - CIOs/CTOs: pilot AI workloads on neutral, multi‑cloud platforms to avoid vendor lock‑in and speed deployment. Expert takeaway Snowflake is well positioned to capture AI‑driven infrastructure spend, but the stock’s premium requires disciplined due diligence and measured position sizing; near‑term momentum should be validated by sustained revenue and retention metrics. What do you think? Share your experience deploying data platforms for AI. — Viktor Kopylov, PhD, CFA.

🚀 Why Snowflake is Disrupting the Entire Data Industry From Data Warehouse to AI Data Cloud: The Revolutionary Evolution 💡 Key Insights Snowflake is no longer just a cloud data warehouse. It has completely transformed into an AI-native data platform. 🔥 Game-Changing Features 1️⃣ Cortex Analyst - Natural Language Data Analysis "Why did Seoul region sales drop last quarter?" → Instant answers without complex SQL 2️⃣ Cortex Search - Hybrid RAG Search Converse with PDF documents like a chat 200ms response time for instant search 12% more accurate search results 3️⃣ AI Functions in SQL sql SELECT AI_SENTIMENT(customer_review), AI_SUMMARIZE(feedback), AI_EXTRACT('complaints', content) FROM customer_data; 📊 Explosive Growth Metrics (2025) Revenue: $3.63B (29.2% ↗️) Large Customers: 580 ($1M+ annual revenue customers) Market Share: 18.33% vs Databricks 8.67% 🥊 vs Databricks: Key Differentiators SnowflakeDatabricksProprietary vectorized engineApache Spark-basedSQL-first, ease of useDeveloper-friendly, flexibilityFully managed serviceOpen-source ecosystem 🚀 Why Should You Care? 1. Data Democratization: Non-developers can perform AI analysis  2. Zero Data Movement: AI processing within security boundaries  3. Instant Deployment: No complex infrastructure required 💼 Real-World Use Cases Customer Service: Auto-classify/prioritize tickets Marketing: Social media sentiment analysis HR: Policy document Q&A chatbots 🎯 The Bottom Line Snowflake is becoming "The Power Grid of the Data Economy" As every enterprise transforms into a data-driven organization, Snowflake is no longer an option but essential infrastructure. Direct analysis of Snowflake's innovation and future outlook from a data analytics software developer perspective. #Snowflake #DataWarehouse #AI #CloudData #BigData #DataAnalytics #TechTrends #DataScience #EnterpriseTech #Innovation

"The Race to Build the Ultimate Data Platform" Blog Just published a blog titled "The Race to Build the Ultimate Data Platform" - exploring how AI demands and efficiency goals are driving the shift from fragmented tools to unified data platforms. Organizations investing in comprehensive platforms gain operational resilience, better governance, and accelerated AI adoption. Read how Amazon Web Services (AWS), Microsoft, Google, Databricks, Cloudera, Qlik, Oracle, and others are competing to build the most comprehensive platforms to support the needs to data driven companies leveraging their enterprise data and AI. Take a look! #DataPlatforms #AI #DataManagement #DigitalTransformation #DataStrategy Enterprise Strategy Group (part of Omdia) https://lnkd.in/eQn4PcWx

How to $30k Monthly In 2026: Compete with Palantir, Google Cloud and Snowflake Using AI This **eye-opening video reveals detailed, practical strategies you can use right now to transform your existing data assets into predictable, recurring income streams, leveraging AI and automation to operate at an enterprise level—even if you’re a solo entrepreneur or small team. Get 100 Free Leads Month at www.datatoleads.com Gone are the days when you needed a massive IT budget and teams of analysts to monetize data. With the right approach and tools, you can now compete with giants like Palantir, Snowflake, and Google Cloud, building your own data commerce empire while keeping overhead low and profits high. ✅ Why traditional big data solutions (Snowflake, Palantir, Google Cloud) were designed for large enterprises—and how 2026’s advancements let small businesses and individual entrepreneurs play at the same level. ✅ How platforms like AvocaData allow you to access, manage, enrich, and resell data without needing complex infrastructure, technical architecture, or advanced coding skills. ✅ How AI-powered automation can replace expensive teams while boosting your capacity to enrich, clean, and package high-value datasets. ✅ Actionable methods to build your own data marketplace or create a white-labeled data resale system for agencies, lead gen companies, and SaaS clients. ✅ Why 2026 is the perfect year to ride the data monetization wave, positioning yourself ahead of the competition and building a long-term, scalable income stream. ✅ Step-by-step frameworks to enrich datasets, resell aged leads, bundle high-demand niches, and leverage AI models for predictive targeting. ✅ How to launch your data monetization business without writing a single line of code, managing complicated ETL pipelines, or requiring enterprise-level funding. With AI automation and advanced platforms like AvocaData, you can: ✔️ Monetize aged leads, phone lists, skip-traced databases, and niche appointment data effortlessly. ✔️ Build predictable recurring revenue while helping businesses lower their customer acquisition costs. ✔️ Enrich and cleanse data to increase its resale value in the mar

How to $30k Monthly In 2026: Compete with Palantir, Google Cloud and Snowflake Using AI This **eye-opening video reveals detailed, practical strategies you can use right now to transform your existing data assets into predictable, recurring income streams, leveraging AI and automation to operate at an enterprise level—even if you’re a solo entrepreneur or small team. Get 100 Free Leads Month at www.datatoleads.com Gone are the days when you needed a massive IT budget and teams of analysts to monetize data. With the right approach and tools, you can now compete with giants like Palantir, Snowflake, and Google Cloud, building your own data commerce empire while keeping overhead low and profits high. ✅ Why traditional big data solutions (Snowflake, Palantir, Google Cloud) were designed for large enterprises—and how 2026’s advancements let small businesses and individual entrepreneurs play at the same level. ✅ How platforms like AvocaData allow you to access, manage, enrich, and resell data without needing complex infrastructure, technical architecture, or advanced coding skills. ✅ How AI-powered automation can replace expensive teams while boosting your capacity to enrich, clean, and package high-value datasets. ✅ Actionable methods to build your own data marketplace or create a white-labeled data resale system for agencies, lead gen companies, and SaaS clients. ✅ Why 2026 is the perfect year to ride the data monetization wave, positioning yourself ahead of the competition and building a long-term, scalable income stream. ✅ Step-by-step frameworks to enrich datasets, resell aged leads, bundle high-demand niches, and leverage AI models for predictive targeting. ✅ How to launch your data monetization business without writing a single line of code, managing complicated ETL pipelines, or requiring enterprise-level funding. With AI automation and advanced platforms like AvocaData, you can: ✔️ Monetize aged leads, phone lists, skip-traced databases, and niche appointment data effortlessly. ✔️ Build predictable recurring revenue while helping businesses lower their customer acquisition costs. ✔️ Enrich and cleanse data to increase its resale value in the mar

How to $30k Monthly In 2026: Compete with Palantir, Google Cloud and Snowflake Using AI This **eye-opening video reveals detailed, practical strategies you can use right now to transform your existing data assets into predictable, recurring income streams, leveraging AI and automation to operate at an enterprise level—even if you’re a solo entrepreneur or small team. Get 100 Free Leads Month at www.datatoleads.com Gone are the days when you needed a massive IT budget and teams of analysts to monetize data. With the right approach and tools, you can now compete with giants like Palantir, Snowflake, and Google Cloud, building your own data commerce empire while keeping overhead low and profits high. ✅ Why traditional big data solutions (Snowflake, Palantir, Google Cloud) were designed for large enterprises—and how 2026’s advancements let small businesses and individual entrepreneurs play at the same level. ✅ How platforms like AvocaData allow you to access, manage, enrich, and resell data without needing complex infrastructure, technical architecture, or advanced coding skills. ✅ How AI-powered automation can replace expensive teams while boosting your capacity to enrich, clean, and package high-value datasets. ✅ Actionable methods to build your own data marketplace or create a white-labeled data resale system for agencies, lead gen companies, and SaaS clients. ✅ Why 2026 is the perfect year to ride the data monetization wave, positioning yourself ahead of the competition and building a long-term, scalable income stream. ✅ Step-by-step frameworks to enrich datasets, resell aged leads, bundle high-demand niches, and leverage AI models for predictive targeting. ✅ How to launch your data monetization business without writing a single line of code, managing complicated ETL pipelines, or requiring enterprise-level funding. With AI automation and advanced platforms like AvocaData, you can: ✔️ Monetize aged leads, phone lists, skip-traced databases, and niche appointment data effortlessly. ✔️ Build predictable recurring revenue while helping businesses lower their customer acquisition costs. ✔️ Enrich and cleanse data to increase its resale value in the mar

How to $30k Monthly In 2026: Compete with Palantir, Google Cloud and Snowflake Using AI This **eye-opening video reveals detailed, practical strategies you can use right now to transform your existing data assets into predictable, recurring income streams, leveraging AI and automation to operate at an enterprise level—even if you’re a solo entrepreneur or small team. Get 100 Free Leads Month at www.datatoleads.com Gone are the days when you needed a massive IT budget and teams of analysts to monetize data. With the right approach and tools, you can now compete with giants like Palantir, Snowflake, and Google Cloud, building your own data commerce empire while keeping overhead low and profits high. ✅ Why traditional big data solutions (Snowflake, Palantir, Google Cloud) were designed for large enterprises—and how 2026’s advancements let small businesses and individual entrepreneurs play at the same level. ✅ How platforms like AvocaData allow you to access, manage, enrich, and resell data without needing complex infrastructure, technical architecture, or advanced coding skills. ✅ How AI-powered automation can replace expensive teams while boosting your capacity to enrich, clean, and package high-value datasets. ✅ Actionable methods to build your own data marketplace or create a white-labeled data resale system for agencies, lead gen companies, and SaaS clients. ✅ Why 2026 is the perfect year to ride the data monetization wave, positioning yourself ahead of the competition and building a long-term, scalable income stream. ✅ Step-by-step frameworks to enrich datasets, resell aged leads, bundle high-demand niches, and leverage AI models for predictive targeting. ✅ How to launch your data monetization business without writing a single line of code, managing complicated ETL pipelines, or requiring enterprise-level funding. With AI automation and advanced platforms like AvocaData, you can: ✔️ Monetize aged leads, phone lists, skip-traced databases, and niche appointment data effortlessly. ✔️ Build predictable recurring revenue while helping businesses lower their customer acquisition costs. ✔️ Enrich and cleanse data to increase its resale value in the mar

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After Databricks’ $100B Milestone, Where Is the Data Cloud Heading? The Wall Street Journal just reported that “Databricks hitting a $100B valuation, driven by explosive demand for AI-driven data platforms, signals a renaissance in how we store, process, and derive value from data. At the same time, Snowflake’s Q2 FY26 was equally striking: $1.14B in revenue (+32% YoY), adjusted earnings of $0.35 per share, and a raised full-year product revenue forecast of $4.4B." These numbers represent more than financial strength, they underscore a broader shift in enterprise data strategies. Looking forward, the data cloud race is transforming: * AI-native platforms will shift from modern ETL to embedded intelligence where LLMs live inside warehouses, enabling on-demand querying, forecasting, and anomaly detection. * Autonomous optimization: think self-scaling warehouses that adjust compute, suspend during idle periods, and optimize cost without human oversight. * Data as a Product: where datasets, pipelines, and analytics systems are governed, cost, owned, and deliver clear ROI driving business value directly. * The convergence of compute, storage, and AI inference, collapsing the silos between analytic, operational, and ML workloads into a seamless, intelligent fabric. In this next era, competition won’t be about features alone, it will hinge on platforms that combine trusted performance, governance, and scalable innovation. Those are the winners that will define the data cloud of the next decade. Read the full article in the first comment.