ThingWorx Analytics Training: Module 1 Part 1
This video begins Module 1: ThingWorx Analytics Overview of the ThingWorx Analytics Training videos. It covers some of the functionality of the ThingWorx platform, as well as ThingWorx Analytics capabilities.
This video does not contain any hands-on exercises, and you don't need access to a running ThingWorx Analytics environment.
This video has chapters — use the chapter menu in the player to jump to any section.
Chapter Summaries
0:00 – Introduction: ThingWorx Analytics Training Modules Overview Kicks off the ThingWorx Analytics training course, previewing the upcoming modules and hands-on exercises, and introducing Module 1 as the platform and analytics overview.
0:19 – Mirror Worlds: Physical-Digital Convergence & the IoT Vision Explains David Gelernter's early-1990s "Mirror Worlds" concept from Yale, showing how connected sensors, cameras, and ubiquitous wireless networks converge the real and digital worlds into smart systems.
1:52 – PTC Strategy: CAD, PLM, IoT & the AR Digital Thread Describes PTC's physical-digital convergence strategy and logo, tracing the digital thread from CAD and PLM design through IoT data capture and back to the physical world via augmented reality.
3:11 – Digital Transformation: Challenges, Threats & Business Outcomes Covers the three industry threats—workforce shortage, cost pressures, and digital disruption—and the four transformation outcomes across products, processes, people, and work sites.
3:59 – What Is ThingWorx Analytics? Machine Learning for IoT Data Defines ThingWorx Analytics as a component of the ThingWorx IoT platform that adds advanced predictive analytics and machine learning to handle the volume, velocity, and variety of IoT data without a data scientist.
4:52 – ThingWorx Platform Capabilities: Connect, Build, Analyze & Manage Outlines ThingWorx's tools for standardizing device connectivity, simplifying connected-app creation, unlocking IoT analytics insights, orchestrating assets and workflows, and empowering the workforce with contextualized data.
5:51 – Industrial Connectivity: ThingWorx Kepware Server, MES, SCADA, PLCs & Industry 4.0 Details how ThingWorx Kepware Server delivers scalable, cost-effective industrial connectivity to legacy and modern factory assets—MES, SCADA, PLCs, and CNCs—enabling predictive maintenance, reduced downtime, and Industry 4.0 projects.
6:57 – Thing Model, Mashup Builder & Composer: Building Digital Twins Introduces the Thing Model as a real-time digital twin, the drag-and-drop Mashup Builder for dashboards and mobile apps, and ThingWorx Composer for model building, service and logic authoring, and system configuration.
8:15 – ThingWorx Analytics Features: Anomaly Detection, Predictive & Prescriptive Modeling Highlights the core analytics capabilities—anomaly and signal detection, predictive modeling and scoring, prescriptive intelligence, alerting and notifications, and automated learning—all requiring no data science expertise.
9:13 – Vuforia Augmented Reality & the Universal Thing Browser Shows how PTC's Vuforia AR technology lets users see, touch, and hear assets while viewing live data, predictions, and alerts, with streamlined digital twin authoring and a universal thing browser that shares asset info across PTC products.
10:27 – Machine Learning Fundamentals: From Passive Information to Proactive Insight Explains machine learning as a form of AI that builds predictive algorithms, using a pump-vibration example to show how analytics surfaces hidden patterns and turns passive information into proactive, deeper decision-making.
12:04 – The Analytics Continuum: Descriptive, Predictive, Prescriptive, Persuasive & Automated Walks through the analytics maturity curve—descriptive/business intelligence, predictive, prescriptive what-if scenarios, persuasive recommendations, and automated analytics—illustrated with a smart-home automation example.
14:45 – Analytics Types & Decision-Making: Descriptive, Diagnostic, Predictive & Prescriptive Compares how descriptive, diagnostic, predictive, and prescriptive analytics each demand different levels of human input, covering standard and ad hoc reports, alerts, drill-downs, factor analysis, forecasting, and optimization.
16:12 – Solving Big Data Challenges: Volume, Velocity & Variety Explains how ThingWorx Analytics tackles big data's volume, velocity, and variety—scaling to massive datasets, automatically keeping predictions up to date, adapting to any data type, and offsetting the shortage of trained data scientists.