The Industrial Internet: The Journey Is Blurry

This is the final post of a five-part weekly series exploring the Industrial Internet in the New Industrial Age. If you missed the beginning of the series, catch up by reading The Journey to the Industrial Internet, The Industrial Internet: The Future Is Big, The Industrial Internet: The Future Is Healthy and The Industrial Internet: The Future Is Cloudy.

Marrying the large data sets that the Industrial Internet creates with Hadoop technology means that the new platform must be cloud-centric. It must support different storage systems and different cloud vendors. It needs to be agnostic so customers can choose to use Amazon, Microsoft or internal solutions for elastic computation and storage. It also has to work seamlessly with operational systems that run at point of equipment.

For example, a SCADA node working on the controls network must process data in real time to ensure that the equipment is running safely and correctly. Data stored for trends and short-term analysis also needs to be local at site, so that normal sub-second response times can be leveraged to make fast-paced decisions. cloud computing GELong-term data storage is best suited for the cloud, where the added computing capacity of Hadoop clusters can be used (not to mention that Hadoop also drops your operational data storage costs). With the need for both local computation and storage and cloud computation and storage, the platform must blur the lines of where data is (local or cloud) and where computation is done (local or cloud). The more these lines are blurred and the more seamless the user experience, the easier it becomes to use the right technology to solve a problem.

The blurring of the lines allows an organization to use the right technology to create the right solution and hide all the technical mumbo-jumbo from the end users. It means that the interaction and integration of existing systems and the cloud must evolve. It means that a new platform is needed to make this practical and easy.

Note: This post is the final post of a five-week series examining the journey of the Industrial Internet

Brian Courtney

A recent transplant to the MidWest, Brian thinks Big Data “rocks.” He’s recently taken the Analytics piece of GE’s business under his wing, so if you have thoughts on any of these – MidWest, Big Data or Predictive Analytics – even rocks – follow Brian on Twitter @brianscourtney.

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