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Kim Devlin-Allen Written by Kim Devlin-Allen, Read the recent blogs posts , press releases and news written by Kim Devlin Allen
on 19 Nov 2019

Getting useful information from your analytics solutions requires vital enabling technologies and inputs. From sensors, gateways, networks, and protocols, to software at the edge and in the cloud, the system architecture and integration can seem complicated. Building your digital solution requires an understanding of both your industry challenges and the technologies available to tackle those issues. 

 

What are the enabling technologies required for your data analytics to drive the best business decisions?

Getting insights from big data using data analytics requires companies to invest in technologies from the edge to the cloud. The critical hardware components at the edge include sensors and actuators. These can be located on fixed, on-site equipment, moving assets, or remote ones in the field. Sensors have become very advanced and can collect information, including proximity, temperature, location, image, vibration, and a host of other analog inputs. And selecting the sensor type and supplier ensures the system has a strong foundation. 

Sensor nodes and gateways at the edge pre-process and aggregate data to send to servers for processing and storage in the cloud or on-premise. Firmware at the edge gateways must support the industrial network communications protocols to integrate well with your factory operations to support the wired or wireless connectivity and analog or digital input/output (I/O) options required. Edge computing capability in the gateway can add flexibility for real-time decisions and minimize network bandwidth. Whether fixed function or flexible, look for a solution that will grow with you along your digital transformation journey. 

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An IoT software platform is a fundamental component to manage and scale the device endpoints in the IIoT network, provide middleware to support cloud or server connectivity, manage data storage, data encryption, data processing, AI algorithms, and analytics. The cloud or on-premise hardware and software must scale to efficiently process and store data for analytics.  Work with your system integration ecosystem partner, to ensure the IoT software platform supports both near-term priorities as well as a long-term roadmap with scalability and flexibility weighed along with the functionality and cost. Finally, ensure the visualization tools help your teams from the operators to the C-Suite make the best decisions for your business.

 

These core elements can enable your analytics solution to deliver an output that drives business decisions and impacts your bottom line.  A strong ecosystem partner can help you assess requirements, prioritize these hardware and software solution elements, review make vs. buy decisions, and customize a solution that grows with your business.

Learn how Cyient works with customers for digital solutions to transform their business in the information age.

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