Analytics and Data Summit 2018

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.

In this session learn about Oracle's soon to be released prepackaged "SaaS on PaaS" cloud applications called "Adaptive Intelligent Applications for Manufacturing". This product is built directly on top of several Oracle’s PaaS components to collect, store, and analyze massive amounts of Operational Technology (OT) data coming from shopfloor systems such as MES, quality systems, LIMS, Equipment, Test stations and contextualizes this data with Information Technology (IT) data residing in HCM/CRM/SCM/ERP applications in a single consolidated operational data store and analyzed by applying advanced analytics, data mining/data science, and AI techniques to discover key patterns and correlations from historical data related to manufacturing efficiencies and also provide actionable predictive analytics to improve yield, reduce defects, reduce scrap, minimize cycle times, manufacturing costs, and equipment downtime.