Transforming Data from Passive to Active Intelligence

A refreshing read on 5 strategies to shatter enterprise inertia from a COO’s lens from IBM Institute of Business Value. Loved the future-ready perspective! From a techie’s viewpoint, here are my key takeaways: 1.Prioritize transformational growth : embrace uncertainty, anticipate market shifts 2.Make operations the data epicenter : design apps with unified, connected data 3.From process architect ➝ operational disruptor : question norms & simplify 4.Embrace AI : explore agentic AI first-use cases 5.Move from AI adopters ➝ AI orchestrators : enable human + AI collaboration for measurable impact Inspiring vision for building resilient, future-ready enterprises! Read more here: https://lnkd.in/g8_FRVDa

Traditional data processing pipelines are dead. Or at least, fundamentally obsolete. For years, we've wrestled with data volume, slicing information into manageable chunks for analysis. This fragmented approach introduced significant overhead and often missed critical cross-contextual insights. Enter Gemini 1.5 Pro's 1-million-token context window. This isn't just an incremental improvement; it's a paradigm shift in how AI consumes and understands information. Imagine feeding an entire codebase, multiple analyst reports, or hours of video into a single model without summarization loss. This capability bypasses the need for complex pre-processing, allowing AI to identify patterns and relationships across truly massive datasets. The implication is profound: AI can now operate at a scale previously unimaginable for deep, singular analysis. This challenges every enterprise data strategy built on aggregation and indexing. Companies failing to adapt their workflows will drown in their own data, while others will unlock unprecedented efficiencies and insights by directly leveraging these expansive context windows. It redefines the architecture of intelligent systems. This isn't just about 'more data'; it's about radically different data interaction. The bottleneck has shifted from data ingestion to intelligent prompt engineering and strategic system design. Are your systems ready for a model that can 'read' your entire company in one go, or are you still relying on fragmented, pre-AI paradigms? #AI #GenerativeAI #LargeLanguageModels #DataStrategy #SystemDesign #Innovation

Exciting news in the software industry! A breakthrough AI algorithm developed by [Source] promises to revolutionize data analysis processes, making them faster and more accurate. This innovation not only enhances efficiency in software development but also opens up new possibilities for AI applications across various industries. How do you think this advancement will impact the future of data-driven decision-making? Share your thoughts! #AI #SoftwareIndustry #Innovation #TechTrends

What role has IBM played in the fan experience at the US Open?  🎾 Host Daniel Newman is joined by IBM GM, Data & AI Ritika Gunnar for a conversation on IBM’s technology partnership with the US Open and the company’s expanding leadership in enterprise data and AI solutions, with a key focus on enhanced fan experiences powered by advanced AI and data innovations. Key Takeaways Include: 🔹AI-Powered Fan Engagement: IBM is introducing new features at the US Open, such as enhanced analytics and interactive AI capabilities, to deepen fan interaction during matches. 🔹Enterprise Data Transformation: Platforms like watsonx.data and IBM’s approach to generative and agentic AI are empowering organizations to derive actionable insights from both structured and unstructured data. 🔹Real-World Automation: Tools like Agent Connect and watsonx Orchestrate are enabling enterprises to streamline operations and automate decision-making, transforming business workflows across various industries. 🔹Strategic Growth: IBM’s acquisition of DataStax underscores a commitment to unifying and leveraging unstructured data at scale, further strengthening the value proposition for enterprise AI applications. Learn more at https://lnkd.in/gAKJYpVx Watch the full video here: https://lnkd.in/dazsY6Qx

Unlock the full potential of your GenAI initiatives by moving beyond pilots into production. The secret? domain-specific, continuous agent evaluations that ensure accuracy, compliance, and trust at scale. ⚡ ✨ Why It Matters 📊 Generic metrics and gut checks can't assess enterprise-specific tasks ⚠️ Lack of rigorous evaluation leads to unpredictable failures and lost confidence 🔄 Continuous optimization turns static tools into ever-learning systems 🔑 Key Principles 🎯 Contextual Metrics: Tailor evaluations to your proprietary data, workflows, and policies 🧠 Systems Thinking: Measure every stage—from query parsing to response—so you can pinpoint and fix issues fast ⚙️ Auto-Optimization: Leverage platforms that learn from user interactions, auto-adjust agent behavior, and focus improvements on high-impact areas 🤝 User Trust: Consistent, transparent performance builds confidence and drives adoption 📈 Organizations that prioritize AI evaluation infrastructure will scale faster, deliver dependable agents, and lead the enterprise AI landscape. 🏆 👉 Dive deeper into how Databricks and Agent Bricks can help you build, monitor, and optimize production-ready AI agents: https://lnkd.in/grH-wSyU #AI #GenAI #MachineLearning #DataBricks #AIAgents #ContinuousImprovement #EnterpriseAI #MLOps Databricks

AI + Graph Meets Unified, Contextualized IT Data Reading Charles’s excellent post on Solving Tech Debt With AI + Graph: Charles Betz [https://lnkd.in/gQTqsaSQ] “What I believe is a powerful new substrate: a unified IT knowledge graph. This may be the true successor to the long-troubled configuration management database (CMDB).” At Flexera, our data strategy is built on one idea: make IT data consistent, contextualized, and connected so it’s truly actionable. Our foundations: Normalize and unify IT assets into a single, consistent view  Add business context (ownership, risk, compliance, cost)  Build relationships across assets, contracts, and dependencies  Power it all with AI + analytics to deliver clear actions and recommendations As Forrester highlights, the future of IT isn’t just collecting data — it’s understanding dependencies and making smarter decisions. At Flexera, our mission is simple: help customers reduce risk, optimize spend, and govern with confidence — powered by trusted, connected data. #TechnologyIntelligence #Flexera #AI #DataStrategy #ITGovernance 

Legacy Databases weren’t designed for today’s problems. Data management is AI driven — and that’s exactly what IntelliDB Enterprise delivers! Auto indexing, auto vacuuming, AI based query optimization, high availability are just some of the features that define IntelliDB as a database and more. It’s also a change in how entire industries are managing and scaling data in the age of A.I. Wave goodbye to antiquated systems. The future is #IntelliDB. #AiStartup #Ai #StartupIndia #TechIndia #IntelliDBEnterprise #AIDriven #SmartData #DatabaseInnovation #EnterpriseSolutions #Database #Management #LegacyDatabase #BuiltOnPostgres

Integrating AI into your data pipelines is no longer just a luxury; it's becoming essential for businesses that want to stay ahead. Research shows that organizations employing AI are 2.5 times more likely to achieve business goals. This underscores the importance of synergy between data management and intelligent systems. Our latest article explores how Cortex AI-SQL simplifies this integration, allowing teams to leverage AI without getting bogged down by complexity. The ability to transform data processes not only enhances efficiency but empowers developers and data scientists to focus on innovation rather than routine tasks. We invite you to read about the implications of this technology and how it can redefine your approach to data management. We'd love to hear your thoughts on how AI is shaping your data strategies. #DataScience #MachineLearning #CloudComputing #AIIntegration #SnowflakeDevelopers https://lnkd.in/dK4fpHCQ

More than half of enterprise leaders plan to boost their data infrastructure spending and in some industries, that’s over $30M a year. Falling behind isn’t an option. Your data stack can be the engine that powers AI, agility, and growth. Explore the 9 proven moves top enterprises are using to build a resilient, real-time, and AI-ready stack. 👉 https://ow.ly/Y2rY50WVG1F #DataEngineering #DataInfrastructure #DataStack #AIReady #EnterpriseAI #DigitalTransformation #grazitti

Why do many AI applications fail before they scale? The reasons are clear: unclear data, weak business alignment, and low user trust. These are not technical glitches but strategic gaps. The solution is to build a strong foundation—governed data, alignment with business priorities, and trust at the user level. With these in place, AI adoption moves from pilots to lasting impact. #AIAdoption #DigitalStrategy #FutureReady