The Industrial Internet of Things (IIoT) is revolutionizing the way we collect, store, and analyze data. With the proliferation of connected devices, organizations are generating massive amounts of data that can be used to improve efficiency, productivity, and safety.
However, traditional data historians are not designed to handle the volume, velocity, and variety of data generated by the IIoT.
This session will explore the limitations of traditional data historians and discuss how next generation data historians can help organizations to:
• Centralize data across multiple sites: Next generation data historians can help organizations to consolidate data from disparate sources into a single repository. This makes it easier to track and analyze data across the entire organization.
• Integrate AI and ML tools for analytics: Next generation data historians can be integrated with AI and ML tools to provide insights that would not be possible with traditional data analysis methods. This can help organizations to identify trends, predict outcomes, and make better decisions.
• Share data with internal and external stakeholders: Next generation data historians can make it easy to share data with internal and external stakeholders. This can help to improve collaboration and communication, and it can also help to drive innovation.
• Future-proof data systems by integrating open-source technologies: Next generation data historians can be built on open-source technologies, which makes them more flexible and scalable. This can help organizations to future-proof their data systems and ensure that they are able to keep up with the ever-growing volume of data.
Takeaways
• Limitations of traditional data historians for centralizing and sharing industrial data
• Centralizing data across multiple sites
• Integrating AI and ML tools for analytics
• Sharing data with internal and external stakeholders
• Future-proofing data systems by integrating open-source technologies