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Forbes
13-06-2025
- Business
- Forbes
Real-Time Data As The Catalyst For Enterprise Intelligence
Gowtham Chilakapati is a Director at Humana. He is an expert in enterprise data and AI systems with a focus on real-time analytics. getty Today's enterprises must operate with the precision of a living organism—continuously sensing change, adapting operations and making real-time decisions to maintain competitive advantage. Success no longer hinges on hindsight dashboards or quarterly reviews; it depends on how intelligently and swiftly an enterprise can respond to the present. Throughout my career, I've focused on re-architecting this responsiveness—not through incremental dashboard upgrades, but by rebuilding the cognitive core of the enterprise, from data pipelines to decision frameworks. Traditional BI systems are rearview mirrors. Informative, yes—but too delayed to navigate the sharp turns of customer behavior shifts, regulatory changes or supply chain turbulence. In contrast, real-time enterprises operate with telemetry-grade awareness, enabling proactive decisions at every node. In one engagement at a national health insurer, for example, my team and I helped transition from legacy batch processing to an event-driven architecture. Real-time synchronization across enrollment, application evaluation and compliance didn't just reduce exception rates and operational costs—it catalyzed a deeper shift in organizational behavior, replacing delay tolerance with an expectation of immediacy. This underscores a key insight: Real-time capability isn't just a technical upgrade—it transforms how an organization perceives and responds to change. Real-time transformation begins with diagnosing lag. Where in your value chain do decisions arrive too late? Then, look for sensory bottlenecks—systems that see data but too slowly. Begin small, prove value and, above all, treat every real-time win as a cultural muscle to be reinforced. AI: Only As Intelligent As The Systems It Touches Too many AI initiatives fail because they bolt intelligence onto the edges—after data's been flattened, delayed and diluted. True enterprise intelligence requires AI embedded within the real-time context: close to the source, close to the user and close to the moment of decision. At Humana, we saw this principle come to life with the deployment of our Perception-Augmented Retrieval-Augmented Generation (P-RAG) systems. Unlike traditional RAG architectures that rely on static search indices, P-RAG systems incorporate contextual signals—like tone, visual cues and system states—directly into the model's reasoning. This allows the AI to adapt in real time to unfolding interactions, delivering responses that are not only faster but also more relevant and human-aware. What sets these systems apart isn't just the efficiency gains. It's the dynamic feedback loop they create: Every interaction makes the next one smarter. The real innovation, then, isn't only technical—it's cultural. Success depends on building a workplace that's ready to trust, iterate and evolve with adaptive intelligence. For teams looking to put this into practice, here are a few key principles: • Start at the edge. Embed AI where decisions happen, not just in analytics labs. • Train in flow. Your model improves only as fast as your feedback loops. • Build for transparency. Traceability and explainability aren't "nice to have" in regulated industries—they're survival traits. Platform Modernization: Not A Lift-And-Shift—It's A Leap In Thinking Cloud migration is not modernization. Moving your data center into someone else's basement changes nothing unless you rethink what your platform means . In every successful initiative, I've found the key is to prioritize platformization —not just migration. That means creating reusable data services, real-time APIs and federated governance structures that allow teams to innovate without reinventing the wheel. Some key steps I've found beneficial when beginning a platformization approach include: • Inventory before investments are made. Use lineage mapping to identify which reports, jobs and APIs are redundant, misaligned or siloed. • Create a capability catalog. Define which services are reusable across business units. • Elevate architecture reviews. Make modernization a governance topic, not just a tech project. In one example, mapping dependencies across membership reporting systems led to the discovery of over 100 redundant SSIS packages. This paved the way for both cloud migration and enterprise simplification. The true unlock? A shared vocabulary of data, enabling agile governance and enterprise-scale observability. From Reporting To Responding: Building The Adaptive Enterprise The future of competitive advantage lies with adaptive enterprises—those that continuously evolve based on real-time insights. The convergence of analytics, AI and platform modernization is forming a digital nervous system for intelligent responsiveness. But beyond tools, this is a cultural transformation. Organizations must embrace: • Responsiveness over rigidity • Continuous learning over static optimization • Signal sensitivity over status reporting This isn't hypothetical. I've led these transformations in highly regulated industries where change isn't just hard—it's expensive. Yet, by aligning tech with truth in real time, these systems become not just efficient, but adaptive and intelligent by design. Success doesn't go to those with the biggest budget or flashiest dashboard—it goes to those who can sense, decide and act at the speed of relevance. That's the future I'm working to build: one signal, one system, one insight at a time. Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?
Associated Press
03-06-2025
- Business
- Associated Press
data.world launches Data Marketplace: A revolutionary e-commerce experience transforms enterprise data discovery
New marketplace experience bridges the gap between technical data catalogs and business user needs, enabling self-service data discovery at scale AUSTIN, Texas, June 3, 2025 /PRNewswire/ -- the enterprise data catalog for the modern data stack, today announced the launch of Data Marketplace, a purpose-built, e-commerce-style discovery experience that transforms how business users find and access high-quality data products within their organizations. The new marketplace serves as a curated front door to comprehensive catalog, displaying only the most trusted and business-ready data assets organized by domain and use case rather than technical structure. Data Marketplace addresses a critical challenge facing enterprise organizations: while 73% of enterprise data goes unused for analytics, business users struggle to navigate the technical complexity of traditional data catalogs. The new marketplace experience removes these barriers by providing a consumer-grade interface that makes data discovery as intuitive as online shopping. 'Organizations have invested heavily in building comprehensive data catalogs, but adoption among business users remains a challenge,' said Brett Hurt, CEO and Co-founder of 'Data Marketplace changes that dynamic by meeting business users where they are—providing a familiar, shopping-like experience that makes our customers' most valuable data products accessible to everyone who needs them.' Bridging the technical-business divide Data Marketplace operates on the principle that different users need different experiences. While data engineers require the full technical depth of a comprehensive catalog, business users need an interface that speaks their language and serves their workflows. The marketplace curates only the highest quality, actively maintained data products and presents them through visual merchandising and domain-based organization. 'Think of it like IKEA,' explained Tim Gasper, Chief Product Officer at 'Your catalog is the warehouse—all the raw materials organized by type and source, perfect for technical teams building solutions. The marketplace is the showroom—curated displays organized by use case and business domain, designed for users who want solutions, not raw materials.' Three pillars of enterprise value Data Marketplace delivers value through three core pillars: Discovery: Simplified decision-making through intuitive domain-based organization, visual merchandising, and curated experiences that surface only explicitly published, high-quality data products. Adoption: Expanded platform reach with consumer-grade user experience, simplified navigation purpose-built for business users, and configurable landing pages with personalized suggestions. Insight: Future-proofed strategy aligned with data mesh and domain-oriented data management practices, efficient governance that balances control with accessibility, and seamless transitions between marketplace and catalog views. Industry-leading innovation Data Marketplace represents continued innovation in making enterprise data more accessible and valuable. Built on the company's unique knowledge graph foundation, the marketplace maintains all the governance, security, and lineage capabilities of the underlying catalog while providing an entirely new user experience optimized for business consumption. 'This isn't just a new interface—it's a fundamental shift in how we think about data accessibility,' said Gasper. 'Instead of expecting business users to become data engineers, we're making data behave like the consumer products they're already comfortable with.' Seamless integration, immediate value Data Marketplace integrates seamlessly with existing deployments, requiring no data duplication or separate maintenance. Data products are created and managed in the familiar catalog environment, then published to the marketplace with a simple status change. This approach ensures organizations can leverage existing investments in metadata and documentation while providing immediate value to business users. Key capabilities include: Supporting data mesh and modern architectures Data Marketplace aligns with emerging industry practices around data products, data mesh architectures, and domain-oriented data management. Organizations implementing decentralized data strategies can use the marketplace to establish standardized approaches to data product creation and promotion while maintaining centralized governance and discovery. Availability and adoption Data Marketplace will be available for private preview to existing customers by the end of June 2025, with public preview following in August 2025. The feature will be included at no additional cost for customers. 'We're seeing tremendous excitement from our customers who are ready to move beyond simply documenting their data to actively promoting and merchandising their most valuable data products,' said Hurt. 'Data Marketplace represents the evolution from data warehouse to data showroom.' About turns data chaos into clarity. We're the most-adopted data catalog and governance platform on the market. Built on a unique knowledge graph foundation, seamlessly integrates with your existing systems. We set the standard for swift, people-centric governance that's both simpler and smarter. We don't just manage data; we unlock its potential, paving the way for responsible AI adoption and data-driven decision-making at scale. As a Certified B Corporation, is committed to fostering global data literacy. With prepare for your data-driven future – where clarity conquers chaos, and every data point tells a story. For more information, visit Contact: Liz Elfman [email protected] View original content to download multimedia: SOURCE
