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Organize and Process IoT Data Quickly Using AWS IoT Analytics

Cloud That

IoT device use has recently increased in applications such as agriculture, smartwatches, smart buildings, IoT retail shops, object tracking, and many more. These Internet of Things devices generate a large amount of data, which is subsequently transported to the cloud to be analyzed. . About CloudThat. Introduction.

IoT 70
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Governments Must Promote Network-Level IoT Security at Scale

Palo Alto Networks

Many governments globally are concerned about IoT security, particularly as more IoT devices are rolling out across critical sectors of their economies and as cyberattacks that leverage IoT devices make headlines. In response, many officials are exploring regulations or codes of practice aimed at improving IoT security.

IoT 86
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Network Security: Predictions for 2021

Palo Alto Networks

Whether applied to cybersecurity, networking, compute, storage or anything else, these technologies give companies the ability to prepare for unpredictability and put in place flexibility. IoT Security: More Important Than Ever. An increasing number of IoT devices will continue to get connected to the enterprise network.

Network 95
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Unlocking the Power of AI with a Real-Time Data Strategy

CIO

Titanium Intelligent Solutions, a global SaaS IoT organization, even saved one customer over 15% in energy costs across 50 distribution centers , thanks in large part to AI. Learn more about moving to cloud-native applications and data with Kubernetes in this blog post.) Kubernetes, containers, and a cloud-native approach will help.

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Are We Prepared to Deal with the Impact of Cyber Threats on 5G?

Palo Alto Networks

From energy to manufacturing, finance to transportation, healthcare to government, we will see processes and behaviours evolve because of 5G. It directly impacts the availability of legitimate services that are running on the IoT devices. appeared first on Palo Alto Networks Blog. This post was originally published by GSMA.

IoT 52
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Digital Transformation is a Data Journey From Edge to Insight

Cloudera

This is the first in a six-part blog series that outlines the data journey from edge to AI and the business value data produces along the journey. STEP 5: Push data to storage solutions. STEP 3: Monitor data throughput from each factory. STEP 4: Capture data from Apache Kafka streams.

Data 112
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5 Ways AI Will Transform the Logistics Industry

Altexsoft

This includes all transactions related to the supply process – from purchase to internal exchanges that include storage, delivery, and auditing. Meanwhile, the system’s Local Clearance Procedure (LCP) is a similar option for the storage of goods before they are released through customs procedures.