Over the past decade, the world has seen an explosion of online and social activity, all of which is generating vast amounts of data. Louis Rossouw surveys the future for insurance.
Big Data is an information technology term describing a dataset that has become so large it is awkward to manage and work with using traditional database techniques.
Collections of large volumes of data present business opportunities. Microsoft’s head of research and strategy expressed it as follows: “The data-centred economy is just nascent. You can see the outlines of it, but the technical, infrastructural and even business-model implications are not well understood right now.”
A McKinsey report on Big Data mentions the following sources of increased volumes of data:
- Companies are capturing data with higher granularity. This means capturing every transaction and interaction with customers, as well as the details on every transaction. Retailers may now have, via loyalty cards, a record of every single item purchased by customers in their stores.
- Social networking is generating vast amounts of data. This includes profile information, details on connections, individual status updates and news items.
- The use of multimedia is also generating vast amounts of data. This ranges from YouTube videos to the medical sector, where medical imaging takes up vast amounts of data.
- More and more devices are also being connected to the internet and generating data. This is known as “The Internet of Things”. The mobile phone is an obvious example of this, but other devices also connect to the internet via mobile phone or directly – including anything from running shoes, pedometers, electronic package labels, car telematics and the internet-connected fridge.
- The report also highlights how data is being generated in all sectors of the economy,not just information technology.
“Self knowledge through numbers” is the motto of a group of people interested in tracking data about themselves and to use this to change and improve their own lives. These individuals track such data as
- Weight and other medical information, e.g, heart rate and blood pressure
- Exercise routines using global positioning systems (GPS), pedometer and similar devices
- General movement and travel tracking using GPS
- Information on diet
- Productivity or efficiency data such as numbers of emails sent
- Softer information, including feelings and attitudes
This data is monitored and visualised, and then self-experimentation is used to see if a variable of interest then improves. This sounds extreme but experimentation may be as simple as measuring the impact of variations of diet on productivity or happiness. It can almost be described as an individualised evidence-based approach.