The intelligent cloud is ubiquitous computing (computing everywhere), empowered by the public cloud (Cloud Computing – see the first blog post) and artificial intelligence (AI) that is a continually expanding set of connected systems and devices, gathering, and analyzing data—close to users, the data, or both. Users get real-time insights and experiences, delivered by highly responsive and contextually aware apps.

Sounds complicated, but in essence, Edge computing allows devices in remote locations to process data at the “edge” of the network, either by the device itself (devices have mini-computers onboard) or a local server. And when data needs to be processed in the central datacenter, only the most important data is transmitted, thereby minimizing latency.

The edge computing framework’s purpose is to be an efficient workaround for the high workload data processing and transmissions that tend to cause significant system bottlenecks. Because applications and data are closer to the source, the turnaround is quicker, and system performance is better.

Sometimes examples speak volumes so when you hear Edge Computing think:

– Voice assistants like Alexa or Siri. They combine voice recognition and process automation algorithms to decode the user’s request and send results of the operation. Imagine what life would be like if every time you made a request to Alexa, it had to be decoded and processed in Amazon’s primary data center along with the millions of other requests – happening every millisecond. You would grow old waiting for a response!

– Retail stores that are thousands of miles away from their primary datacenter use wireless point-of-sale devices to instantly process payments.

– Kiosk machines you use at the airport or supermarket process your requests connected to the peripherals found on the machine.

– Autonomous vehicles use edge computers that gather data produced by the vehicle’s sensors and cameras and process and analyze it to make decisions in a few milliseconds.

– Wearable IoT devices like smartwatches monitor the user’s health and even save lives.

The interconnectivity of the cloud enabled a more thorough approach to capture and analyze data. With edge computing, things have become even more efficient. Edge computing is a viable solution for data-driven operations that require lightning-fast results and an elevated level of flexibility.

Edge computing also introduces an entirely new level of data and devices to capture, manage and secure, requiring advanced integration capabilities to harness the power of the rich information gathered. With OneVuex in combination with Microsoft solutions, integrating data produced by edge computing can be faster and easier, producing tremendous insights and conveniences with less expense. Let us help you with your integration strategies so you can focus on what you do best – not IT.

Carolyn Bass

VP, Marketing Bass International Software

The intelligent cloud is ubiquitous computing (computing everywhere), empowered by the public cloud (Cloud Computing – see the first blog post) and artificial intelligence (AI) that is a continually expanding set of connected systems and devices, gathering, and analyzing data—close to users, the data, or both. Users get real-time insights and experiences, delivered by highly responsive and contextually aware apps.

Sounds complicated, but in essence, Edge computing allows devices in remote locations to process data at the “edge” of the network, either by the device itself (devices have mini-computers onboard) or a local server. And when data needs to be processed in the central datacenter, only the most important data is transmitted, thereby minimizing latency.

The edge computing framework’s purpose is to be an efficient workaround for the high workload data processing and transmissions that tend to cause significant system bottlenecks. Because applications and data are closer to the source, the turnaround is quicker, and system performance is better.

Sometimes examples speak volumes so when you hear Edge Computing think:

– Voice assistants like Alexa or Siri. They combine voice recognition and process automation algorithms to decode the user’s request and send results of the operation. Imagine what life would be like if every time you made a request to Alexa, it had to be decoded and processed in Amazon’s primary data center along with the millions of other requests – happening every millisecond. You would grow old waiting for a response!

– Retail stores that are thousands of miles away from their primary datacenter use wireless point-of-sale devices to instantly process payments.

– Kiosk machines you use at the airport or supermarket process your requests connected to the peripherals found on the machine.

– Autonomous vehicles use edge computers that gather data produced by the vehicle’s sensors and cameras and process and analyze it to make decisions in a few milliseconds.

– Wearable IoT devices like smartwatches monitor the user’s health and even save lives.

The interconnectivity of the cloud enabled a more thorough approach to capture and analyze data. With edge computing, things have become even more efficient. Edge computing is a viable solution for data-driven operations that require lightning-fast results and an elevated level of flexibility.

Edge computing also introduces an entirely new level of data and devices to capture, manage and secure, requiring advanced integration capabilities to harness the power of the rich information gathered. With OneVuex in combination with Microsoft solutions, integrating data produced by edge computing can be faster and easier, producing tremendous insights and conveniences with less expense. Let us help you with your integration strategies so you can focus on what you do best – not IT.

Carolyn Bass

VP, Marketing Bass International Software

The intelligent cloud is ubiquitous computing (computing everywhere), empowered by the public cloud (Cloud Computing – see the first blog post) and artificial intelligence (AI) that is a continually expanding set of connected systems and devices, gathering, and analyzing data—close to users, the data, or both. Users get real-time insights and experiences, delivered by highly responsive and contextually aware apps.

Sounds complicated, but in essence, Edge computing allows devices in remote locations to process data at the “edge” of the network, either by the device itself (devices have mini-computers onboard) or a local server. And when data needs to be processed in the central datacenter, only the most important data is transmitted, thereby minimizing latency.

The edge computing framework’s purpose is to be an efficient workaround for the high workload data processing and transmissions that tend to cause significant system bottlenecks. Because applications and data are closer to the source, the turnaround is quicker, and system performance is better.

Sometimes examples speak volumes so when you hear Edge Computing think:

– Voice assistants like Alexa or Siri. They combine voice recognition and process automation algorithms to decode the user’s request and send results of the operation. Imagine what life would be like if every time you made a request to Alexa, it had to be decoded and processed in Amazon’s primary data center along with the millions of other requests – happening every millisecond. You would grow old waiting for a response!

– Retail stores that are thousands of miles away from their primary datacenter use wireless point-of-sale devices to instantly process payments.

– Kiosk machines you use at the airport or supermarket process your requests connected to the peripherals found on the machine.

– Autonomous vehicles use edge computers that gather data produced by the vehicle’s sensors and cameras and process and analyze it to make decisions in a few milliseconds.

– Wearable IoT devices like smartwatches monitor the user’s health and even save lives.

The interconnectivity of the cloud enabled a more thorough approach to capture and analyze data. With edge computing, things have become even more efficient. Edge computing is a viable solution for data-driven operations that require lightning-fast results and an elevated level of flexibility.

Edge computing also introduces an entirely new level of data and devices to capture, manage and secure, requiring advanced integration capabilities to harness the power of the rich information gathered. With OneVuex in combination with Microsoft solutions, integrating data produced by edge computing can be faster and easier, producing tremendous insights and conveniences with less expense. Let us help you with your integration strategies so you can focus on what you do best – not IT.

Carolyn Bass

VP, Marketing Bass International Software

The intelligent cloud is ubiquitous computing (computing everywhere), empowered by the public cloud (Cloud Computing – see the first blog post) and artificial intelligence (AI) that is a continually expanding set of connected systems and devices, gathering, and analyzing data—close to users, the data, or both. Users get real-time insights and experiences, delivered by highly responsive and contextually aware apps.

Sounds complicated, but in essence, Edge computing allows devices in remote locations to process data at the “edge” of the network, either by the device itself (devices have mini-computers onboard) or a local server. And when data needs to be processed in the central datacenter, only the most important data is transmitted, thereby minimizing latency.

The edge computing framework’s purpose is to be an efficient workaround for the high workload data processing and transmissions that tend to cause significant system bottlenecks. Because applications and data are closer to the source, the turnaround is quicker, and system performance is better.

Sometimes examples speak volumes so when you hear Edge Computing think:

– Voice assistants like Alexa or Siri. They combine voice recognition and process automation algorithms to decode the user’s request and send results of the operation. Imagine what life would be like if every time you made a request to Alexa, it had to be decoded and processed in Amazon’s primary data center along with the millions of other requests – happening every millisecond. You would grow old waiting for a response!

– Retail stores that are thousands of miles away from their primary datacenter use wireless point-of-sale devices to instantly process payments.

– Kiosk machines you use at the airport or supermarket process your requests connected to the peripherals found on the machine.

– Autonomous vehicles use edge computers that gather data produced by the vehicle’s sensors and cameras and process and analyze it to make decisions in a few milliseconds.

– Wearable IoT devices like smartwatches monitor the user’s health and even save lives.

The interconnectivity of the cloud enabled a more thorough approach to capture and analyze data. With edge computing, things have become even more efficient. Edge computing is a viable solution for data-driven operations that require lightning-fast results and an elevated level of flexibility.

Edge computing also introduces an entirely new level of data and devices to capture, manage and secure, requiring advanced integration capabilities to harness the power of the rich information gathered. With OneVuex in combination with Microsoft solutions, integrating data produced by edge computing can be faster and easier, producing tremendous insights and conveniences with less expense. Let us help you with your integration strategies so you can focus on what you do best – not IT.

Carolyn Bass

VP, Marketing Bass International Software

The intelligent cloud is ubiquitous computing (computing everywhere), empowered by the public cloud (Cloud Computing – see the first blog post) and artificial intelligence (AI) that is a continually expanding set of connected systems and devices, gathering, and analyzing data—close to users, the data, or both. Users get real-time insights and experiences, delivered by highly responsive and contextually aware apps.

Sounds complicated, but in essence, Edge computing allows devices in remote locations to process data at the “edge” of the network, either by the device itself (devices have mini-computers onboard) or a local server. And when data needs to be processed in the central datacenter, only the most important data is transmitted, thereby minimizing latency.

The edge computing framework’s purpose is to be an efficient workaround for the high workload data processing and transmissions that tend to cause significant system bottlenecks. Because applications and data are closer to the source, the turnaround is quicker, and system performance is better.

Sometimes examples speak volumes so when you hear Edge Computing think:

– Voice assistants like Alexa or Siri. They combine voice recognition and process automation algorithms to decode the user’s request and send results of the operation. Imagine what life would be like if every time you made a request to Alexa, it had to be decoded and processed in Amazon’s primary data center along with the millions of other requests – happening every millisecond. You would grow old waiting for a response!

– Retail stores that are thousands of miles away from their primary datacenter use wireless point-of-sale devices to instantly process payments.

– Kiosk machines you use at the airport or supermarket process your requests connected to the peripherals found on the machine.

– Autonomous vehicles use edge computers that gather data produced by the vehicle’s sensors and cameras and process and analyze it to make decisions in a few milliseconds.

– Wearable IoT devices like smartwatches monitor the user’s health and even save lives.

The interconnectivity of the cloud enabled a more thorough approach to capture and analyze data. With edge computing, things have become even more efficient. Edge computing is a viable solution for data-driven operations that require lightning-fast results and an elevated level of flexibility.

Edge computing also introduces an entirely new level of data and devices to capture, manage and secure, requiring advanced integration capabilities to harness the power of the rich information gathered. With OneVuex in combination with Microsoft solutions, integrating data produced by edge computing can be faster and easier, producing tremendous insights and conveniences with less expense. Let us help you with your integration strategies so you can focus on what you do best – not IT.

Carolyn Bass

VP, Marketing Bass International Software

The intelligent cloud is ubiquitous computing (computing everywhere), empowered by the public cloud (Cloud Computing – see the first blog post) and artificial intelligence (AI) that is a continually expanding set of connected systems and devices, gathering, and analyzing data—close to users, the data, or both. Users get real-time insights and experiences, delivered by highly responsive and contextually aware apps.

Sounds complicated, but in essence, Edge computing allows devices in remote locations to process data at the “edge” of the network, either by the device itself (devices have mini-computers onboard) or a local server. And when data needs to be processed in the central datacenter, only the most important data is transmitted, thereby minimizing latency.

The edge computing framework’s purpose is to be an efficient workaround for the high workload data processing and transmissions that tend to cause significant system bottlenecks. Because applications and data are closer to the source, the turnaround is quicker, and system performance is better.

Sometimes examples speak volumes so when you hear Edge Computing think:

– Voice assistants like Alexa or Siri. They combine voice recognition and process automation algorithms to decode the user’s request and send results of the operation. Imagine what life would be like if every time you made a request to Alexa, it had to be decoded and processed in Amazon’s primary data center along with the millions of other requests – happening every millisecond. You would grow old waiting for a response!

– Retail stores that are thousands of miles away from their primary datacenter use wireless point-of-sale devices to instantly process payments.

– Kiosk machines you use at the airport or supermarket process your requests connected to the peripherals found on the machine.

– Autonomous vehicles use edge computers that gather data produced by the vehicle’s sensors and cameras and process and analyze it to make decisions in a few milliseconds.

– Wearable IoT devices like smartwatches monitor the user’s health and even save lives.

The interconnectivity of the cloud enabled a more thorough approach to capture and analyze data. With edge computing, things have become even more efficient. Edge computing is a viable solution for data-driven operations that require lightning-fast results and an elevated level of flexibility.

Edge computing also introduces an entirely new level of data and devices to capture, manage and secure, requiring advanced integration capabilities to harness the power of the rich information gathered. With OneVuex in combination with Microsoft solutions, integrating data produced by edge computing can be faster and easier, producing tremendous insights and conveniences with less expense. Let us help you with your integration strategies so you can focus on what you do best – not IT.

Carolyn Bass

VP, Marketing Bass International Software