Kinetica, a leader in active analytics for the Extreme Data Economy, announced the release of the first complete active analytics platform, dramatically simplifying the architecture to deliver smart analytical applications at massive scale.
The platform unites the key elements of active analytics: historical analytics, streaming analytics, graph analytics, location intelligence, and machine learning-powered analytics. Enterprises use the platform to build smart analytical applications that capture data, continuously assess it and automatically react – revolutionizing the pace and potential of businesses across industries.
The Fourth Industrial Revolution is about data. Success in every industry depends on recognizing data as the most valuable corporate asset,” said Paul Appleby, CEO at Kinetica. “From smart cities to autonomous vehicles, logistics to retail, finance to healthcare, organizations that build smart, analytical applications to make decisions instantly shape markets, threaten incumbents, and drive new business models centered around data.”
Traditional approaches to analytics (passive analytics) were designed before the rise of the Internet of Things (IoT), artificial intelligence and location intelligence. Businesses are left with assorted analytics technologies that struggle to align and apply advanced analytical techniques effectively. With an active analytics approach, businesses build smart applications that assess and act on data instantaneously. Examples include:
- Finance: Institutional investors continuously assess value at risk via models in the background as an ongoing process, shifting from a stale view of risk to a dynamic, responsive view triggered by market events.
- Automotive: Automakers recognize unique driving behavior and the conditions that led to it to make more responsive route recommendations, learn how people drive in various scenarios, and ultimately build a better vehicle.
- Retail: Retailers build evolving customer profiles that update as shopping takes place, reacting to customer location, time, price points, preferences, history, and immediate situation, among others, in order to tailor offers and interactions and glean more about the target audience.
- Telecommunications: Telco service providers analyze streaming mobile signals to understand network demand versus coverage, in order to better target the network to users and reduce massive infrastructure costs.
Every industry knows they need active analytics, but they run up against several challenges. It’s difficult to analyze streaming and historical data simultaneously at scale, to incorporate location intelligence into smart apps, to integrate machine learning into production applications, and to stitch together a hodgepodge of technologies that weren’t designed for active analytics,” said Nima Negahban, CTO at Kinetica. “Organizations are demanding a unified active analytics platform for historical analytics, streaming analytics, location intelligence, graph analytics, and machine learning, and that’s what we’ve delivered with the Kinetica Active Analytics Platform.”
The Kinetica Active Analytics Platform is enterprise-grade, cloud-ready, and GPU-accelerated. It is used to build custom applications for real-time business decisions, in the context of historical information, utilizing machine learning-powered analytics.
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