dbSeer’s Post

A biotech firm faced fragmented data across siloed systems, delaying critical reporting and analytics. SingleStone’s AI-driven solution built a unified enterprise domain model and modernized their data warehouse, slashing reporting delays and enabling real-time insights. This transformation boosted decision-making speed, operational efficiency, and innovation, positioning the firm for growth. By integrating AI, SingleStone turned data chaos into a strategic asset. The result? Faster, smarter analytics that drive competitive advantage. How could unified data transform your organization’s efficiency? https://loom.ly/r9X7_h4

❄️ Snowflake Cortex: Conversational AI for the Enterprise Snowflake’s new Cortex Agent moves beyond traditional BI and into the era of agentic AI—where natural language becomes the interface for enterprise data. 🔹 How it works → Plans & executes multi-step workflows (structured + unstructured data) Uses Cortex Analyst (SQL/BI) + Cortex Search (unstructured/documents) Generates charts, summaries, and SQL directly from user prompts Secure by design: role-based access, masking, auditability 🔹 For leaders → Accelerates decision-making with governed, explainable AI. 🔹 For developers → REST API with streaming responses (text, SQL, visualizations) makes it simple to embed into apps or chat UIs. This isn’t just incremental BI—it’s data intelligence operationalized. 📖 Full article here: https://lnkd.in/gkiRFx3K #Snowflake #Cortex #EnterpriseAI #DataStrategy #Analytics #AI

The data lake vs. data warehouse debate misses the point entirely. Both approaches treat data as isolated records. Neither captures the business context that makes data actionable. Here’s an insight into what a Business Ontology is, why it matters and how it’s a foundational step to leverage your data The future belongs to enterprises that don't just collect data, they understand it. Oraion is how you get there. Read more here: https://lnkd.in/eSBD3Zzj) #datawarehouse #datalake #AI #LLM #businessontology

DataOps.live launches Momentum to help enterprises operationalize their data for trusted AI at scale - https://lnkd.in/ddh8Bj8j Nick Halsey, CEO of DataOps.live, says, "With Momentum, we’re giving CDOs and data leaders the visibility, automation, and governance they need to trust their data, their AI outputs, and the data products that deliver them." #Automation #Data #AI #EnterpriseAI #DataOps #TechIntelPro

“Trusted data is table stakes. It’s the foundation for every strategic data solution that our customers have built. But today, trust alone isn’t enough." Introducing the Semarchy Data Platform: helping enterprises accelerate the delivery of data products, reduce risk in AI initiatives, and unlock greater value from their data investments. 📢 Read the release in our newsroom and register to join our launch event at 11am ET today https://lnkd.in/ea3KxhcX

💡 AI and open-source are transforming enterprise data platforms in 2025 and businesses that adapt early are gaining a real competitive edge. At PaperTrail, we see this trend reflected every day: companies need flexible, intelligent, and unified data solutions to unlock the full value of their information. Here are three key takeaways from the recent Forbes article, “AI And Open Source Redefine Enterprise Data Platforms In 2025”: ✅ Scalable and Adaptive Platforms: Modern enterprise data platforms leverage AI and open-source technology to scale quickly and adapt to evolving business needs, reducing reliance on rigid legacy systems. ✅ Cost Efficiency and Operational Agility: By integrating AI-driven automation and open-source tools, businesses can process and structure data more efficiently 📈, cutting operational costs 💰 while improving decision-making speed. ✅ Data as a Strategic Asset: Structured, searchable and enriched data becomes a cornerstone for innovation, powering analytics, AI agents, and better collaboration across departments 🤝. PaperTrail is at the forefront of this shift, transforming unstructured documents into a unified, actionable knowledge base. #papertrailgr #fromdatatoknowledge #AI #datamanagement https://lnkd.in/dCUBFR6V

Solving Supply Chain Challenges with Data-Driven Intelligence – Practical Steps to Unlock the Value of Supply Chain Data - At InterSystems READY 2025, a recurring message resonated across sessions: the most significant barriers in supply chains today are not futuristic, nor are they rooted in the complexity of AI models. Instead, they lie in the foundational issues of fragmented, inconsistent, and unreliable data. The session “Solving Supply Chain Challenges with Data, Driven Intelligence” focused […] The post Solving Supply Chain Challenges with Data-Driven Intelligence – Practical Steps to Unlock the Value of Supply Chain Data appeared first on Logistics Viewpoints . #Logistics #SupplyChain #CarolTrans

Most BI tools can show you the data. Agentic BI asks: “What do you want to do with it?” That shift from static reporting to intelligent, autonomous action isn’t theoretical anymore. It’s being built right now. Databricks just published a great piece on Agentic BI; what it is, why it matters, and how to get there. Spoiler: it’s not just about AI. It’s about unifying your infrastructure, data, and semantics into a system that can reason, plan, and act. Here’s what stood out to me: “Without unified semantics, your agent may be able to analyze, but it won’t understand.” That hits home. At Collectiv, we see this gap all the time. AI initiatives that stall not because the model is wrong, but because the foundation is fractured. Agentic BI isn’t something you buy. It’s something you build strategically, and step by step. This article is a great starting point: https://loom.ly/iEQHQ2g Where are you seeing the biggest barriers between insight and action in your org? #AgenticBI #Databricks #GenAI #SemanticModeling #DataStrategy #BIArchitecture #Collectiv #ThoughtLeadership

Really great piece by Jonathan Reichental, Ph.D. on how relatively simple AI techniques can unlock real value from data governance before complexity and cost overwhelm the effort. Here's a few takeaways from what HEMOdata see happening in this space: - The increased emphasis on quick wins. Many companies postpone tasks like automating metadata creation, classification, lineage and so on because they feel too tedious but the truth is they provide IMMEDIATE value. - How building frameworks now (even if they're not perfect) pays dividend by creating visibility, reducing risk and more steadily enabling AI & analytics. - The idea that better governance isn’t just about compliance or risk-mitigation but about enabling innovation. When your data is organized, you move faster with more confidence. Where HEMOdata make a difference: - We help organizations leverage smart metadata management so data assets become discoverable with richer context & without manual overhead. - Our focus on data lineage & classification alongside leveraging our partner solutions make it easier to show where data came from, how it’s used and who owns or is accountable for it. Immediate visibility here often gives leadership the confidence to invest further. - Once the basics are in place the scalability of governance is realized and adding newer AI models, data sources or regulatory pressures becomes a lot less painful. Some common blockers we see: - IT / data teams may see governance differently than business units. It’s often necessary to make a clear business case (not just risk) to get buy-in from stakeholders. - Over-engineering can stall momentum so you want frameworks that evolve by keeping governance light but effective. - Ensuring tools & processes support continuous monitoring. Because governance isn’t a “one and done” thing. Trends, regulations & data volumes keep shifting. In short, if your organization is trying to unlock value from data, start with the simple AI-enabled governance moves. They offer low risk, fast benefits and lay the foundation for more advanced analytics and innovation. At HEMOdata, we’re here to help companies move from “messy, manual data” toward “trusted, usable data.” Excited to see how this space continues to evolve. https://lnkd.in/eZ4eKBvf #HEMOdata #datagovernance #AI #data

Big Data 75: Companies Driving Innovation in 2025 - Database Trends and Applications: Research and Markets predicts trends during this time will include AI and machine learning integration, cloud-based big data services, edge analytics, ... #bigdata #cdo #cto