Remove Experimentation Remove IoT Remove Testing Remove Visualization
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Full Steam Ahead: CIO Kopal Raj of WABTEC on staying ‘on-track’ with AI, IoT and sustainability goals

CIO Business Intelligence

Our products are sometimes tested for a year before being launched in the field. Our command centres monitor a large number of freight locomotives across the globe, allowing us to visualize the locomotive’s location, and its servicing alerts. Much of the digitization in the manufacturing segment is related to the execution systems.

IoT 85
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The DataOps Vendor Landscape, 2021

DataKitchen

Testing and Data Observability. DataOps needs a directed graph-based workflow that contains all the data access, integration, model and visualization steps in the data analytic production process. It orchestrates complex pipelines, toolchains, and tests across teams, locations, and data centers. Testing and Data Observability.

Testing 300
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Interview with: Sankar Narayanan, Chief Practice Officer at Fractal Analytics

Corinium

In the long run, we see a steep increase in the proliferation of all types of data due to IoT which will pose both challenges and opportunities. Fractal’s recommendation is to take an incremental, test and learn approach to analytics to fully demonstrate the program value before making larger capital investments.

Insurance 250