Defects in Traditional IT Modes
Flexible and low cost
For entrepreneurs engaging in Wi-Fi businesses, searching for machine rooms, renting racks, purchasing servers and installing systems in the initial start-up phase of a business proves to be highly costly, in terms of both the time and capital involved. In addition, it is difficult to quickly expand the network, server and database resources as the business grows.
Server, network and database resources are ready for use out of the box, can be activated after just a few minutes, and be flexibly re-sized based on the development of the business. The IT costs, operation and maintenance workforce and system deployment time are reduced by 50%, 80% and 90% respectively compared with those in traditional IT models.
Difficulties in the storage and querying of mass data
Based on the requirements for industry supervision and business development, users' recent access records will be saved for querying in specific scenarios. In traditional IT models, the storage of mass data resulted in high costs, but offered poor performance in querying.
Alibaba Cloud data centers in every region provide multi-line BGP network access. Optimal network quality is guaranteed for Wi-Fi access points connecting to the cloud Wi-Fi platform from either a fixed or mobile network. Alibaba Cloud is gradually rolling out more overseas data centers to support the global business expansion of Wi-Fi service providers.
Weak analytical capability of big data
Mass data processing
Wi-Fi users' web access records and tracking mass data are accumulated by Wi-Fi service providers. However, most Wi-Fi service providers lack the capability to analyze this big data, making it difficult to conduct an in-depth analysis of WIFI users, or cash in on WIFI data.
Alibaba Cloud Distributed Relational Database Service is capable of effectively resolving the issues surrounding the storage and querying of mass quantities of users' web behavior data. Alibaba Cloud's open data processing service (ODPS), on the other hand, can effectively solve the difficulties of storing and analyzing mass amounts of history data.