Suppose we have a massive amount of sensor data available. Good right? Yes... but there is still a caveat. A critical concept which is unknown to or misunderstood by many at both IT as well as OT side: that concept is context. Context is what anchors digital data to...
One of the most frequent questions you'll hear—often from well-meaning CFOs or project sponsors—is this: "What's the ROI of this platform?" It's a fair question. It's also a tricky one. The uncomfortable truth is that foundational investments rarely yield immediate,...
The digital revolution has transformed many industries, yet manufacturing and critical infrastructure continue to lag behind. Compared to sectors like finance or retail, which have rapidly embraced digital technologies, manufacturing remains deeply rooted in legacy...
The First Movers are those companies and industries that embraced automation early on, often starting with widespread deployment of PLCs and other control systems long before digitalization became a buzzword. These organizations have had decades to build up...
Time for a short thought experiment. You are asked to make a presentation on the top 5 reasons to invest in a digital transformation program. What would you write down? Resist the urge to read on for just a couple of seconds and try to answer this question in your own...
Before we delve into what many consider the fourth industrial revolution, we will quickly review the ones that came before it. Manufacturing has been the driver in the development of the industrial revolutions and adoption of new technology. The steam engine, the...
We are talking Data, AI and IT-OT Convergence with Dan Jeavons, president of Applied Computing and formerly the VP of Computational Science and Digital Innovation at Shell.
We are diving into the real-world struggles when integrating IT and OT from the perspective of another super interesting end-user!
From building Northvolt’s digital backbone from scratch to helping smaller manufacturers unlock the value of their data, Anton Melander’s journey is a masterclass in scaling fast and learning hard!
From spreadsheets to AI co-workers: Nathalie Rigouts on what it really takes to turn data into value in industry.
Let’s go a bit more technical in this one 😁. With our new Capability Map just being published, we wanted to get some more insights in the connectivity part… so let’s talk OPC UA and MQTT!
We talk about Platforms that Empower, About People-AI and AI-AI interaction, Context and much more with Accenture’s Zev Arnold.
We’re diving into OT Cyber Security for the first time (but definitely not the last!) with Danielle Jablanski and talk about The Good, the Bad, and the Pointless Deliverables.
Digital solutions should not be front and center. People and processes should be. This episode is all about Lean, Culture and Operational know-how!
We are sitting down with Alexander Krüger to talk about something that’s both old and revolutionary in the industrial world: open source software.
Introducing the ITOT.Academy: a live learning program built for IT and OT professionals who want to actually make collaboration work. No buzzwords, just practical and fun stuf to get you started today
We talk all things IoT and Cyber Security with Olivier Bloch and Ryan Kershaw in this new IT/OT Insider podcast
Nikki brings a refreshing and much-needed OT floor-level perspective. Her world is HMI screens, SCADA, machine builders, and the hard truths about where industry transformation actually stands today!
Yes, MES Matters! But how do you get started? Join us in this new episode with David and Mat Barber!
We talk about the Power of Happy Accidents, preparation over prediction and how modular systems and composable strategies can future-proof organizations.
We’re diving into visibility, traceability, and real-time analytics of Parts with Tim Butler, CEO and founder of Tego.
We talk about the history and future of MQTT and HiveMQ, about why every company is becoming an IoT Company and more!
We explore the CONNECT industrial intelligence platform with Roberto Serrano Hernández and Clemens Schönlein
We talk to Anupam Gupta, Co-Founder & President North Americas at Celebal Technologies, to discuss how enterprise systems, AI, and modern data architectures are converging in manufacturing.
We’re joined by David Rogers, Senior Solutions Architect at Databricks and talk about AI, data governance, and cloud-scale analytics.
We talk to Evan Kaplan – the CEO of InfluxData – on all things data, but more specifically his Silicon Valley view on the industrial world.
In this episode we engage with Geoff Nunan, CTO and co-founder of Rize, to explore the complexities of industrial data management.
In this episode we talk to Joel Jacob about Splunk’s growing focus on OT.
Our guest today is John Younes, Co-founder and COO of Litmus, a company that has been at the forefront of industrial data platforms for the past 10 years.
Network segmentation in OT divides industrial networks into isolated zones, reducing cybersecurity risks and preventing unauthorized access to critical systems.
SCADA is a system used for monitoring and controlling industrial processes, allowing operators to manage infrastructure in real-time through centralized software.
An expert system in industry is an AI-based decision-support tool that mimics human expertise to optimize manufacturing, maintenance, and process control.
A data lake stores raw, unstructured industrial data for flexible analysis, while a data warehouse structures data for predefined queries and reporting.
The Purdue Model for ICS structures industrial control systems into hierarchical levels, improving security, network segmentation, and operational efficiency.
Zero Trust Security in OT applies strict access controls, continuous verification, and network segmentation to protect industrial environments from cyber threats.
MQTT (Message Queuing Telemetry Transport) is a lightweight messaging protocol used in Industrial IoT for real-time, efficient, and secure data communication between devices.
The Purdue Model for Cybersecurity structures industrial networks into hierarchical zones, implementing security controls to mitigate cyber threats and improve resilience.
A Security Operations Center (SOC) for OT is a dedicated cybersecurity hub that monitors, detects, and responds to threats targeting industrial control systems (ICS) and OT networks.
The ISA/IEC 62443 standard provides cybersecurity guidelines for industrial control systems (ICS), ensuring secure design, implementation, and operation of OT environments.
Unified Namespace (UNS) provides a centralized, real-time data structure, while OPC UA is a standardized communication protocol that enables secure data exchange between industrial devices.
Deep learning in manufacturing uses AI algorithms to analyze complex industrial data, automate processes, and improve quality control, predictive maintenance, and robotics.
A Unified Namespace (UNS) in IIoT is a centralized data architecture that organizes and distributes real-time industrial data across connected IIoT devices and enterprise systems.
Edge computing in manufacturing refers to processing data closer to the source, such as machines and sensors, instead of relying on centralized cloud systems.
ISA-95 is an international standard that defines best practices for integrating enterprise IT and industrial control systems, ensuring consistent data flow in manufacturing environments.
An IT/OT convergence strategy outlines the approach for integrating IT and OT systems to enhance data flow, cybersecurity, and industrial automation capabilities.
We’re joined by Aron Semle, CTO at HighByte, to discuss how contextualized industrial data, Unified Namespace, and Edge AI are transforming IT/OT collaboration.
AI in manufacturing uses artificial intelligence technologies such as machine learning, computer vision, and predictive analytics to optimize production processes and quality control.
Computer vision in quality control uses AI-powered image processing and deep learning to inspect products for defects, ensuring consistency and improving manufacturing efficiency.
An IT/OT roadmap is a strategic plan that outlines how organizations will integrate IT and OT systems, improve security, and enhance industrial automation over time.
The Purdue Model for IT/OT security defines a structured approach to segmenting IT and OT networks, reducing cybersecurity risks and enhancing industrial system protection.
A data map in industrial systems is a structured representation of data flow and relationships between different OT and IT systems, enabling better data management and integration.
Industrial data analytics involves collecting, processing, and analyzing manufacturing and operational data to improve efficiency, quality, and predictive maintenance.
Natural Language Processing (NLP) in manufacturing enables AI-powered analysis of text and voice data, improving predictive maintenance, quality control, and human-machine interaction.
An IT/OT convergence framework is a structured model that guides organizations in integrating IT and OT systems, ensuring interoperability, security, and efficiency.
API integration in industrial systems connects different software applications, enabling seamless data exchange and automation between IT and OT environments.
An industrial data lake is a centralized repository that stores large volumes of raw, unstructured industrial data for advanced analytics and AI-driven insights.
IT/OT alignment ensures that information technology (IT) and operational technology (OT) teams collaborate effectively to improve efficiency, security, and data integration in industrial settings.
An industrial protocol is a standardized communication system that enables data exchange between industrial devices, machines, and control systems in automation environments.
In this 3th episode, we sit down with Andrew Waycott and discuss all things AI
The Purdue Model in Industrial Cybersecurity applies security principles to the Purdue Network Model, mitigating cyber risks in industrial automation and control systems.
Advanced Process Control (APC) is a set of technologies that use real-time data and predictive analytics to optimize industrial processes and improve efficiency.
An example of a Unified Namespace is a real-time data hub that integrates SCADA, MES, ERP, and IoT data into a single structured namespace, improving visibility and automation.
An enterprise operational data platform centralizes industrial and business data, enabling seamless integration, real-time analytics, and enterprise-wide automation.
The Purdue Reference Architecture is a hierarchical model that defines industrial automation levels, improving security, data flow, and network segmentation in OT environments.
An operational intelligence platform provides real-time analytics and insights, enabling industrial organizations to optimize performance, security, and decision-making.
IT/OT Convergence is the integration of Information Technology (IT) and Operational Technology (OT) to enable seamless data exchange, improved efficiency, and enhanced security in industrial environments.
An Industrial Data Platform is a centralized system that aggregates, processes, and contextualizes operational and business data from industrial assets.
A cloud-based operational data platform centralizes industrial data in the cloud, enabling real-time monitoring, analytics, and AI-driven automation.
Unified Namespace Architecture is a data structuring approach that centralizes and standardizes real-time industrial data for seamless communication across IT and OT systems.
An Operational Data Platform is a specialized data management system designed for industrial environments.
Despite its foundational role in industrial security and automation, the Purdue Model has limitations in modern digital transformation.
A digital supply chain leverages Industry 4.0 technologies, such as IoT, AI, and cloud computing, to improve visibility, efficiency, and decision-making in supply chain operations.
A real-time operational data platform provides instant access to live industrial data, enabling quick decision-making, process automation, and predictive analytics.
In this episode we talk to Martin Thunman, CEO and co-founder of Crosser about data in motion, IT and OT silos and more!
IT/OT governance defines the policies, standards, and frameworks for aligning IT and OT systems to ensure security, compliance, and operational efficiency.
The Purdue Network Model structures industrial control systems (ICS) into secure layers, ensuring proper segmentation, data flow, and cybersecurity best practices.
OT threat detection refers to cybersecurity practices that identify and mitigate cyber threats targeting operational technology (OT) environments, including SCADA, ICS, and industrial IoT systems.
Industry 4.0 focuses on smart manufacturing with automation, IoT, and data analytics, while Industry 5.0 emphasizes human-machine collaboration and sustainability.
An enterprise data platform for manufacturing centralizes industrial data, providing real-time analytics and AI-driven insights for smarter decision-making.
The Purdue Security Model is a cybersecurity framework based on the Purdue Network Model that protects industrial systems by enforcing network segmentation and access controls.
The Purdue Model for IIoT Security applies layered security controls to protect Industrial IoT (IIoT) environments from cyber threats, ensuring safe data exchange between IT and OT systems.
The Purdue Model for OT Security provides a structured framework to protect operational technology (OT) systems by isolating IT and OT layers and enforcing cybersecurity controls.
A digital twin in manufacturing is a virtual representation of a physical asset, process, or system that enables real-time monitoring, simulation, and optimization.
An AI-driven operational data platform integrates artificial intelligence with industrial data, enabling predictive analytics, automation, and process optimization.
A Unified Namespace organizes real-time industrial data for immediate use, while a data lake stores raw data for later processing and advanced analytics.
Industrial automation refers to the use of control systems, robotics, and AI-driven technologies to automate manufacturing and industrial processes, reducing human intervention and improving efficiency.
A Unified Namespace for Industry 4.0 is a structured data model that integrates real-time industrial data across smart manufacturing systems, enabling automation, AI, and analytics.
The Purdue Model is a hierarchical framework for industrial control systems that defines security zones and data flow between enterprise and operational networks.
In this episode, David and Willem take you behind the scenes of their Industrial Data Platform Capability Map—a structured way to understand how organizations can truly leverage their industrial data. David talks about the role of a platform and which capabilities are needed to build it. He also focuses on the role of Data Management and how that is linked to building a Unified Namespace.
A data diode is a cybersecurity device that ensures one-way data flow, protecting industrial control systems (ICS) from external cyber threats and unauthorized access.
An IT/OT integration strategy defines how businesses align IT and OT systems, ensuring smooth data flow, interoperability, and cybersecurity in industrial environments.
Autonomous manufacturing uses AI, robotics, and IoT to enable self-optimizing production systems with minimal human intervention, enhancing efficiency and adaptability.
Interoperability in IT/OT systems refers to the seamless integration and communication between IT (business systems) and OT (industrial control systems) for improved efficiency and decision-making.
The Purdue Security Framework is a cybersecurity model that enhances the traditional Purdue Model by incorporating modern security principles, including Zero Trust and network segmentation.
A data historian is a specialized database designed to store, retrieve, and analyze historical industrial process data for performance optimization and regulatory compliance.
DataOps for industrial data is a methodology that applies DevOps principles to data management in manufacturing.
A Unified Namespace for Manufacturing integrates real-time production data into a centralized structure, enabling automation, AI-driven analytics, and process optimization.
A Manufacturing Execution System (MES) is software that monitors, tracks, and controls manufacturing operations to improve efficiency, quality, and compliance.
An OT data platform is a specialized system that collects, contextualizes, and processes operational technology (OT) data for industrial automation and analytics.
OPC UA (Open Platform Communications Unified Architecture) is an industrial communication protocol that ensures secure, platform-independent data exchange between devices and systems.