The growth of smart sensors powered by the Industrial Internet of Things (IIoT) has created an influx of data, but if that data is trapped in silos it is of limited value.

In order to unlock the hidden opportunities for improvements and drive real business value, companies require a solution that can provide a holistic view of how they’re operating and get this information to the right person at the right time for improved decision making.  

Elliot Middleton explains how to extract value from industrial big data with contextualized data management and predictive analytics

Simple and Secure

A big data management solution, such as a data historian, consolidates disparate data across the plant or enterprise to effectively bridge the IT/OT divide. For a smooth implementation, select a solution that integrates with your existing equipment and infrastructure. Solutions that offer extensive native interfaces and connections to industry-standard protocols such as OPC can speed up implementation times and help you get the most out of your existing investments.

In the IIoT age, security and safety of industrial data is critical and some organizations are understandably hesitant about consolidating their data in one area. Industrial data can contain valuable intellectual property and organizations are increasingly targets for cybercriminals. It’s important to choose a vendor with rigorous data security protocols for information in transit and at rest to ensure sensitive data is not damaged or stolen.

Enhance Data Accessibility 

Data historians can be deployed on-premises, in the cloud, or in a hybrid model. If operational overhead is a concern, consider a cloud deployment to lower the IT and system maintenance costs borne by your business. If you want to improve collaboration between teams, or empower staff to be active participants in real-time work streams, then look to include mobile applications. Mobile apps help increase operational visibility and enable plant staff to access relevant KPIs and operational benchmarks anywhere, anytime and from any device.

Regardless of deployment model, having a big data management solution enables increased access to data across the enterprise and heightened visibility into performance. This helps users better understand their business, what’s happening, what’s happened and what is likely to happen, which results in improved decision making.

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  Industrial Information Management Infographic

Unlock Value with Context and Analytics

Once data is stored and made accessible, advanced analytics can unlock valuable insights in industrial data. Trending and visualization tools enable users to view real-time and historical data, identify problems, and discover where improvements can be made. Connection to both plant and enterprise data sources simultaneously reveals how disparate operations impact each other. Such tools enable users to monitor production, materials consumption, quality, energy utilization and more – and quickly share that data with relevant staff. By employing advanced analytics organizations can more easily optimize their processes and reap the benefits of reduced operational costs and energy usage, along with improved uptime and regulatory compliance.

Predictive asset analytic tools help improve reliability, performance and availability by providing early warning notification of equipment problems. This enables more proactive, or predictive maintenance to reduce costs and ultimately achieve maximum return on asset investments.

Wonderware offers a comprehensive portfolio of big data management and analytic solutions. With our trusted solutions you can analyze your big data down to the most miniscule details to discover the trapped value within your organization.

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Industrial Information Management Infographic

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