Xanadu for Big Data + IoT + Deep Learning + Cloud Integration Strategy

-- You're invited to the August Meet of Deep Learning in Production in New York. --

Alex G. Lee, a managing partner of Xanadu Big Data, LLC, will talk about Xanadu technology and use cases for Big Data + Deep Learning + Cloud + IoT Integration Strategy.

Contents:

Big Data in IoT & Deep Learning

• Challenges of IoT Big Data Analytics Applications

• Challenges of Cloud-based IoT Platform

• Cloud-based IoT Platform Use Case: GE Predix for Smart Building Energy Management

• Fog/Edge Computing & Micro Data Centers

• Deep Learning for IoT Big Data Analytics Introduction

• Deep Learning for IoT Big Data Analytics Use Case

• Distributed Deep Learning

• Big Data + IoT + Cloud + Deep Learning Insights from Patents

• Big Data + IoT + Cloud + Deep Learning Strategy Development

• Designing Data-Intensive Applications

• Xanadu Functionality

• Xanadu Use Case

• Xanadu + Deep Learning + Hadoop Integration

Xanadu is the most advanced big data management platform technology that is developed to take care of the requirement of high speed processing of diverse type of high volume data. Xanadu can provide a massively scalable fault tolerance system that can connect multiple storages. Xanadu can provide high throughput and low latency data management system. Xanadu provides ACID compliance data management system. Xanadu is designed to be a composable architecture in order to be selected and integrated with other big data system elements such as IT infrastructures and data analytics to satisfy specific big data use requirements. Xanadu is designed for the heaviest workloads that can supports concurrent queries without conflict. For example, Xanadu can support thousands of sensors accessing and updating data at the same time. Thus, Xanadu enables real-time IoT analytics for industrial IoT applications. Xanadu also can support data-intensive distributed deep learning applications involving massive volume multimedia data.

Find us in room 220 at 6.

Sam