Unlike oil, the amount and complexity of data being created is increasing dramatically: predictions suggest that the total amount of global data could grow by about 40% year on year for the next decade.
This increase has been attributed to a number of factors, including the creation of new data sources such as smartphones, increased technical capacity to store and analyse data, and rapid adoption of new forms of communication such as social media.
It has led to the concept of ‘big data’: that is, data on a scale or of a complexity that makes it challenging to use. Such data often requires innovative techniques to extract insights from it (‘big data analytics’).
Estimates suggest that use of big data could contribute £216 billion to the UK economy between 2012 and 20117, and generate 58,000 new jobs. However, the extent to which the opportunities presented by big data will be realised remains unclear.
Storing, analysing and interpreting these unprecedented quantities of data has a number of policy implications.
It can be difficult to find individuals with the unusual combination of skills and knowledge required to manage and make sense of big data. This typically includes specialist methodological expertise, computer programming, and field-specific knowledge and communication skills. A 2014 survey of UK companies implementing big data analytics found that 77% had difficulty recruiting big data staff, and forecasts suggest that demand for big data staff will grow by an average of 23% per annum from 2013-20.
Big data may have the potential to make infringements of privacy more likely for several reasons. The widespread adoption of devices such as GPS-enabled smartphones, which collect and transmit information about their location, is leading to data being acquired from previously private areas of life.
In addition, big data projects often involve re-using data, which may increase the likelihood of original data-usage permissions being lost or overlooked. Projects may also link together different sets of data, which could make it possible to re-identify individuals from data that originally had identifying details removed to protect privacy.
A range of tools and procedures can be used to reduce the risk of data being accessed and used without permission, including data encryption and implementation of good data governance.
This includes making individuals accountable for data security, minimising the number of people with access, and deleting data when appropriate.
However it is impossible to guarantee that data will be completely secure.
There are a number of cases of big data leading to unintended discrimination. For example, it may be used to facilitate differential pricing, where individuals are offered different prices for online products depending on how affluent they appear to be.
Recent developments in data legislation
Use of data in the UK is governed by multiple pieces of legislation, depending on the type of data and the context in which it is being used.
The collection, storage and processing of personal information is regulated by the Data Protection Act 1998, which implements the EU Directive 95/46/EC.
This Directive is widely recognised as being outdated.
Draft proposals to reform it were put forward in 2012, and they are still under discussion by the European Parliament and the Council of the EU.
Interception of communications data in the UK is governed by the Regulation of Investigatory Powers Act 2000.
A 2006 European Commission Directive was incorporated into UK law in 2009, requiring communication service providers to retain communications data for up to two years.
This was struck down by the European Court of Justice in 2014, leading to emergency legislation that the UK Government stated was necessary to retain existing powers.
The Data Retention and Investigatory Powers Act was passed by Parliament in July 2014. It contains a sunset clause, meaning that the laws will lapse at the end of 2016.
Examples of big data applications
- Electioneering – Barack Obama’s 2012 presidential election campaign used data from social media and the party’s database to look for correlations in past voter characteristics and behaviour, enabling them to build up profiles of potential supporters and target resources more efficiently.
- Product design – Bentley Motors has used high performance computing to model components before manufacture, enabling faster product development times, decreasing the number of prototypes required and reducing costs.
- Marketing – An individual’s specific internet browsing history and social media profile can be compared with aggregated data about other customers’ purchases to see what similar customers have bought and to tailor advertising accordingly.
- Asset management – Rolls-Royce collects and analyses data from sensors on its fleet of jet engines to determine when they require servicing.