The internet of things has certainly become an essential part of Big Data. It will also be a key trend in 2018 and beyond. For example, it can be utilized by retailers to establish their competitive edges, such as store location, stock and store management and customer relationship. A company has to be flexible enough to turn the data into valuable business insight and action.
Artificial intelligence caught increased market attention last year. All of a sudden, the public has shown great interest in self-driving cars, self-service supermarkets, etc. All these scenarios might come true within five to ten years.
Cloud computing has continued to gain traction. Hybrid cloud combines the merits of public cloud and private cloud. Local data management can be added on top of convenience and flexibility. Both efficiency and security are critical. Therefore, the era of obsession with cloud computing will be over.
In the meantime, the concept of data analysis will also see a shift. Shall we need more historical data or more real-time analysis? A former chief data analyst of LinkedIn has concluded data analysis into two criteria. It has to be fast and accurate in real-time response, as well as slow and extensive when covering a wide range of data.
Also, data visualization will have wide applications apart from data analysis. Visualization models are becoming more popular, and they enable companies to find new perspectives.
Machine learning technology is developing very rapidly. A lot of non-structural data such as texts, pictures, video, audio, facial expressions and geographical locations have added new dimensions to data analysis. All these elements should not be ignored in the digital economy era.
The role of business operators and senior management won’t be replaced by robots. But artificial intelligence will help business find opportunities and reduce mistakes.
This article appeared in the Hong Kong Economic Journal on Jan 4
Translation by Julie Zhu
[Chinese version 中文版]
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