Many people are excited about data, particularly when those data are big. Big data, we are told, will be the fuel that drives the next industrial revolution, radically reshaping economic structures, employment patterns and reaching into every aspect of economic and social life.
The numbers are certainly impressive. In 1946, one of the first computers weighed 30 tonnes and could do 500 calculations per second. Today, IBM’s ‘Watson’ supercomputer can process 500 gigabytes of data per second. Every day, 39 per cent of the global population use the internet. Facebook has more than 1.3 billion active users, and after the United States the countries with the most subscribers are India, Brazil and Indonesia. In 2007, Twitter had 400,000 tweets per quarter. By 2013, there were 500 million per day. Ninety per cent of data in existence were created in the past two years, and the quantity is doubling every two years. The size and cost of storage has fallen by a third every year since the 1970s, making it possible to store these vast new pools of data. New statistical techniques and tools such as machine-learning algorithms can process and analyse these data dynamically, at a scale and speed that would have been unimaginable just a few years ago.
These changes are already having major effects and will continue to do so. Beyond that little is clear, however. In the world of data, size obviously matters. But how much will it matter in the end, in what ways will these effects be felt and by whom. Perhaps most importantly, what can be done to influence this? While considering the potential impacts of big data in a broad sense, this paper applies these questions specifically to developing countries.