AWS urges enterprises to step up digital transformation with cloud services
Max Wang, Taipei; Willis Ke, DIGITIMES
Enterprises can leverage external cloud resources to accelerate digital transformation at lower IT cost to boost competitiveness, according to Zhang Xia, chief Greater China enterprise cloud computing consultant at Amazon Web Services (AWS).
Zhang said that digitalization is entering a golden development, with new techs and innovations proliferating in the applications fields of AI, big data, IoT, blockchain, 3D printing, and Industry 4.0 smart manufacturing. This has posed challenges to IT system managers at enterprises in meeting ensuing requirements for IT architecture upgrades.
According to his observations, Zhang said, most enterprises have two major goals to accomplish from digital transformation. One is to lower existing technology development expenses and explore new business development possibilities, and the other is to boost customer satisfaction through business innovation and transformation. How to achieve a balance between the two goals will determine whether enterprises can successfully complete digital transformation, Zhang commented.
In order to help enterprises reduce the cost and time needed for their next-generation IT deployments, Zhang revealed, AWS has kept optimizing its cloud computing and storage technologies and services after advancing to the world's leading position in cloud services.
He said that AWS's cloud technology platforms come in a total of 125 categories, covering infrastructure facilities, core services, security and analysis. In 2017 alone, the company launched as many as 1,430 new services, and cloud computing can integrate containerization, function, AI, big data analysis, IoT and edge computing to further drive digitalization progresses at enterprises.
In addition, AWS provides customers with customized GPU, FGPA, containerization, serverless computing and edge computing equipment for integration with AI, and its cloud service systems can also support multiple application architectures including TensorFlow to satisfy upper-layer AI applications such as computer vision, voice recognition and speech recognition.