2019 Cybersecurity Trends to Alert Businesses – Part 2
February 6, 20192019 Trends for the Cloud – Part 2
February 12, 2019Cloud architecture has greatly evolved since the first services were offered about 10 years ago. Subsequently, cloud technology has been adopted by a wide range of organizations. Below are some of the key applications of cloud computing.
• Analysis of big data for predictive purposes
• Audio and video streaming
• Data backup, storage, and recovery
• Development of new services and apps
• On demand delivery of software
• Website and blog hosting
Platform as a Service (PaaS) and Infrastructure as a Service (IaaS) have seen substantial growth in the past few years. In order to remain competitive, companies must implement the accessibility and high performance provided by the cloud.
5G Cellular Issues
Teaming cloud technology and 5G will offer significantly greater capacity and capabilities to IoT (Internet of Things). Providing infrastructure with swifter mobile connections, 5G lets network users upload and stream video faster and with less latency. In addition, 5G is capable of connecting more devices to the internet at a swifter rate. However, there are issues facing 5G acceptance – implementation will be expensive, the FCC scrapped net neutrality regulations, and there are environmental and health issues. These issues will greatly impact 5G, and it could take years before it is used nationally and globally.
AI (Artificial Intelligence)
Utilizing AI for processing Big Data is perhaps the most important development in the gathering of data for business intelligence, resulting in a more informed approach for companies. A well-designed AI platform allows greater speed, efficiency, and effectiveness for the collaboration of data scientists and staff members. This can decrease costs through the prevention of duplicative efforts, better task distribution, automation of basic tasks, faster completion rates, and acquiring labor-intensive tasks such as data duplication and extraction. Moreover, AI can provide support for data governance, ensuring best practices are being implemented by AI and machine learning engineers.
Part 2 will discuss Data Containers, Greater Capacity, Hybrid Cloud, IoE, and Serverless Computing.
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