View or webinar on demand "How to Maximize your Edge Data" June 19. Whether you're just starting to collect data and want to maximize its potential or you're deep into your digital transformation journey and aiming to harness AI at the edge, this webinar provides actionable insights applicable to every stage of your enterprise’s edge journey.
To:
- Understand what drives successful Edge Computing deployments, and identify the right technology and platform.
- Discover how companies spanning the energy, manufacturing, and utilities industries have leveraged their own data to improve the performance of their operators and increase reliability.
- Explore each stage of a digital journey to build an intelligent edge and grasp the importance of addressing infrastructure requirements early on.
As the number of Industrial IoT devices surpasses 30 billion, extracting valuable insights from growing edge data is crucial for organizations to remain competitive.
However, despite this growth, less than 25% of the data collected from IoT devices is processed or ever processed. The main bottleneck? Many enterprises lack the necessary infrastructure to harness their data effectively.
While Edge Computing has rapidly become a vital component of the digital transformation roadmap of industries, barriers such as data silos, scalability issues, fragmented technologies, security concerns and the quest for an optimal edge architecture are holding back their digital transformation.
By 2025, 75% of enterprise-managed data will be processed at the edge and by 2026, at least 50% of Edge Computing deployments will involve machine learning (ML).
It is not too late. Whether you're just starting to collect data and want to maximize its potential or you're deep into your digital transformation journey and aiming to harness AI at the edge, this webinar will provide actionable insights for every stage of your digital edge journey.
At this webinar, we'll explore the challenges faced by leading organizations in their digital journey, from data collection to on-site analytics and real-time inferencing.
Some companies within manufacturing and critical infrastructure are located in the Dark Edge. They have sensor data and controls focusing on specific equipment, with little information leaving the location.
Some others have a Connected Edge, where sensor data is digitized, normalized and streamed to the cloud (Internet of Things IoT); and applications, data and commands are sent to the edge.
Other companies have advanced towards having a more Informed Edge. This occurs when sensor data is filtered and pre-process at the edge for key events and the results are sent to the cloud for further analysis.
The next step is when companies can programme certain actions based on the results of data processing at the edge. This is what we refer to when we talk about the Reactive Edge.
And the end of the journey is when companies can deploy and orchestrate AI and ML models at the edge for real-time inferencing allowing companies to act proactively not reactively.
Digital edge use cases aren’t static and evolve over time. Companies in their digital transformation journey start in the Dark edge, where nothing is connected, to transition to a more connected and intelligent edge where advanced applications and AI-based models are integrated into operational processes.
Looking into manufacturing and utilities for instance, both are already doing automation at the “edge” in the form of programmable logic controllers and other OT. However, these technologies tend to be OT-specific and use embedded software for continuous improvement functions. For manufacturing, Edge Computing enables connectivity and automation for efficiency, improved quality, improved safety, and agility and speed in operations.
Within energy and utility companies, Edge Computing allows them to have greater visibility on their distributed assets and leverage real-time monitoring and automated responses to balance supply and demand. Furthermore, leading grid operators are already deploying AI models to prevent outages.
There are unique challenges and risks associated with Edge Computing solutions.
1. Managing and Orchestration at the Edge. Edge Computing requires zero-touch remote management to scale, sometimes across different geographies, with nodes that can be mobile or have intermittent connection.
2. Securing the edge. Edge Computing extends the perimeter of risk that an enterprise needs to protect, with defense in depth.
3. Managing distributed data. Data created at the edge is different — high-volume, noisy, locally specific, and ephemeral. Edge Computing creates a massive, distributed data challenge in governance and distributed data integration. Automated decisions about which data to preserve, how long to preserve it, when to use data for ML training and when to discard it are critical to balance the cost and efficiency of the edge.
4. Relying on an Edge Platform. Focusing on use cases is not enough. Enterprises need to have a platform and strategic mindset when they deploy edge solutions to enable evolution and design for scale - setting up with the right infrastructure requirements.
Barbara offers a secure industrial edge platform, along with centralized management to scale. With Barbara, companies turbocharge their deployments to production and leverage the full potential of AI without compromising their security and operational efficiency. Organizations can:
1. Deploy real-time AI applications taken from legacy or next-generation distributed industrial assets.
2. Run, debug, and operate it easily for a wide range of devices, networks, and protocols.
3. Manage and protect their deployments with cybersecurity mechanisms designed according to Industry standards.
For more information visit us: www.barbara.tech
For leaders digitally transforming their operations in order to drive predictable, peak performance with minimal risk, Stratus ensures the continuous availability of business-critical applications by delivering zero-touch computing platforms that are simple to deploy and maintain, protected from interruptions and threats, and autonomous. For over 40 years, Stratus has provided reliable and redundant zero-touch computing, enabling global Fortune 500 companies and small-to-medium sized businesses to securely and remotely turn data into actionable intelligence at the Edge, cloud and data center—driving uptime and efficiency. For more information, please visit www.stratus.com or follow Stratus on Twitter @StratusAlwaysOn and LinkedIn @StratusTechnologies.