SUNNYVALE, Calif., Oct. 19, 2016 /PRNewswire/ -- LogtrustTM (www.logtrust.com), the Real-time Big Data-in-Motion as-a-Service solution for Fast Data, Big Data analytics, announced that it will present at IoT Tech Expo 2016 in Santa Clara. On October 21, 2016 at the Santa Clara Convention Center, Logtrust CMO Eric Tran-le, former VP of Cloud Management Services at Oracle, will discuss the need for virtual data models to make sense of multi-IoT event streams under a "single pane," enabling any company - from SMBs to global enterprises - to quickly extract and act on real-time insights. During the presentation, which is part of the conference's Data & Security track, attendees will learn how IoT can bring retail shelves to life and monitor wind farms in real-time -- delivering business value to analytics, field operations, and across organizations and third-party partners.
"When it comes to acting on IoT insight, the business model of today's global organization presents a challenge," explained Tran-Le. "From refrigerators to heavy industrial machinery, most companies rely on local contractors to service their equipment. This means that any proactive maintenance program requires the ability to share data in real-time with third parties under a data model that ensures not just efficiency, but legality."
Tran-Le will discuss how companies can overcome these challenges in order to quickly identify and address equipment, supply chain and other problems, as well as identify and act on efficiency and revenue opportunities. Additionally, Logtrust will exhibit at Stand #88, demoing its platform in manufacturing, marketing and energy industry-related IoT scenarios.
Rapid time-to-value for IoT analytics
Logtrust serves a global set of clients including niu Solutions and Telefonica, enabling them to collect, visualize and analyze massive amounts of data at high speed to act on real-time insights. Logtrust compresses the time-to-value from months/years to days/minutes for IoT analytics, allowing companies of any size to:
- Concurrently ingest up to 10 terabytes per day from a limitless variety of sources while processing and analyzing up to 1 million events per second per core
- Visualize, correlate, and analyze all of the organization's data, regardless of format, drilling down and across to extract signals from noise and quickly identify trends
- Extract "events of interests" from Data Lakes and publish them to external subscribers, such as third party contractors and advertising/marketing partners
- Scale linearly and predictably, expanding to meet business demands while containing costs
Available in any combination of native cloud, hybrid and on-premise deployment, Logtrust provides an end-to-end platform to collect, store and analyze data that's production-ready in minutes, for immediate, actionable IoT insight.
Logtrust is a Real-Time Big Data-in-Motion platform offering Fast Data, Big Data analytics through a solution that enables real-time analytics for operations, fraud, security, marketing, IoT and other aspects of business. Recognized by CIO Review as one of the Top 100 Most Promising Big Data Solution Providers of 2016, Logtrust is intuitive, interactive, and collaborative, with no coding required, guided widgets, and out-of-the-box advanced interactive contextual dashboards. The platform provides a completely real-time experience, with new events always available for query and visualization, and pre-built queries always updated with the most recent events. The highly customizable solution works non-intrusively with your system, with agentless collectors and forwarders, platform remote APIs to check health, and all capabilities callable via REST APIs. Service is always on with cross-cloud region disaster recovery, and data is always hot and unmodified (to meet data reliability and integrity compliance requirements). Logtrust is located at the epicenter of Silicon Valley in Sunnyvale, CA, and further serves its global clients through offices in Boston, Philadelphia, New York, and Madrid. Visit www.logtrust.com for more information.
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