Abstract

The term “Fourth Industrial Revolution” was coined by World Economic Forum (WEF) chairman Klaus Schwab in 2015. He describes it as an exponential growth of several key technological fields’ concepts, such as smart materials and blockchain technology. The effects of technologies have provided new avenues of data for official statistics, which can then be harnessed through the power of data science. At its core, data represents a post-industrial opportunity. Data is increasingly building upon who we are, who we know, where we are, have been, and where we plan to go. Mining and analyzing this data lets us understand and predict how people behave at the individual, group, and global levels. These swathes of new digital data are as valuable for official statistics. However, the volume and variety of data have far outstripped the capacity of manual analysis. As data continue to grow in size and complexity, new algorithms need to be developed so as to learn from diverse data sources. The limitation of conventional statistics in managing and analyzing big data has inspired data analysts to venture into data science. Data Science combines multiple disciplines that use statistics, data analysis, and machine learning to analyze data, and extract knowledge and insights from it. This invited paper session highlights: the new data ecosystem available for timely policy and decision-makers as the world moves into the fourth industrial revolution in which mobile communications, social media, and sensors are blurring the boundaries between people, the Internet, and the physical world; the role of statistics and Statisticians in data science, and various opportunities for official statistics