Analytics and Data Summit 2018

In this presentation, Gary Crisci, Principal Data & Information Architect/Oracle Ace and Shyam Nath, Director-IoT, will walk you through GE’s Predix platform; a cloud based solution that can capture industrial data for various Edge devices. We will discuss scenarios for utilizing this valuable information, including how you get it in the hands of the people who need it, and into a tool that allows them to use the information to make better decisions.

We will illustrate how we capture industrial data from sensors using GE’s Predix cloud platform to determine leading indicators of when large maintenance events are likely to be due and what will be the nature of the maintenance required. We will then demonstrate how to transfer the data into Oracle PBCS for Planning and Budgeting purposes.

No hype cycles or predictions of a gazillion things here. IoT is big. You get it. You know your business and have great ideas for a business transformation strategy. What comes next? Time to make it happen! We present a step-by-step plan to develop your technology implementation strategy on the Oracle Cloud. We discuss the evaluation of communication standards and IoT messaging protocols, data analytics considerations, edge-to-cloud technical architecture, IoT platform selection, end-to-end security, enterprise systems integration and monetization techniques. Seize market opportunities by following our methodology to design and implement a systems architecture that meets complex demands for security, flexibility, durability, and scalability.

This Panel will be lead by the the Authors of the recently published book called "Architecting the Industrial Internet." This session will cover:
1) How and Why Industrial Internet is different from consumer IoT?
2) Why Platform approach to IoT?
3) Big Data and Industrial Analytics
4) Use Cases / Case Studies
5) Professional implications of IoT

Modern global supply chains are highly complex ecosystems. Despite decades of innovations to streamline and optimize operations, companies still consistently face challenges with end-to-end visibility, product tracking, bootlegging, fraud, compliance, safety, and delivery speed. Supply chain-related crimes and disruptions cost companies billions of dollars annually across the globe.

This session showcases how blockchain, IoT and machine learning can be harnessed to fight some of the key supply chain risks and challenges of today.  When implemented right, this solution improves customer trust, minimizes losses and optimizes end to end operations. The session will cover the use cases, technical architecture and implementation considerations.

While AI/ML has matured enough to solve many real-world problems effectively, this process typically requires close interactions between three separate skill sets – the domain expert, the data scientist and the programmer. A typical IoT user is a line-of-business person such as a Plant Supervisor or a Fleet Manager. AutoML enables automatic selection of the most appropriate algorithm that suits the domain problem learned based on the interactions with domain expert. Also, AutoML automatically selects the hyper parameters and tunes the models without requiring data scientist skills. Furthermore, AutoML automates the repetitive analytics needed for retraining models warranted by the high velocity IoT data. Therefore, AutoML is the key enabler of analytics in the industrial IoT. Since the typical business benefits in IoT involve significant savings, IoT is the killer use case for AutoML. We will present how Oracle IoT Cloud applies AutoML for industrial IoT problems.