The final phase is the "plateau of productivity" – the phase where useful applications of the idea finally become mainstream. The curve then bottoms out in a "trough of disillusionment" (phase three), after which there's a slow but steady rise in interest (the "slope of enlightenment" – phase four) as companies discover applications that really do work. First, there's the "trigger" that kicks off the feverish excitement and leads to a rapid escalation in public interest, which eventually leads to a "peak of inflated expectations" (phase two), after which there's a steep decline as further experimentation reveals that the innovation fails to deliver on the original – extravagant – claims that were made for it. It is a graph that describes the life cycle of a technological innovation in five phases. Signatories commit to taking account of the potential wider impacts of their analysis and to using their skills to help those who could benefit the most.įull disclosure: I spent the last four days in Washington DC attending the Teradata Partners' Conference at the expense of Teradata Europe, Middle East and Asia.A concept of enduring utility rarely emerges from the market research business, but the Gartner hype cycle is an exception that proves the rule. This ideology was yesterday given substance when leading British data scientist Duncan Ross launched the 'Doing good with analytics' pledge. US firm Teradata, for example, impresses upon its data scientists that simply obeying privacy laws is not enough - they should take Google's 'don't be evil' motto one step further, using their work to make a positive change.
These datasets often contain detailed and potentially revealing information about us, giving rise to concerns over the implication for privacy, and this an issue taken seriously by firms working with big data. US organisation aWhere is carrying out similar work, and in one of flagship projects uses data from satellite imagery to find and map pools of stagnant water in developing nations that could become breeding grounds for malaria-carrying mosquitos. There are a number of other organisations working towards similar goals, including DataKind, whose founder Jake Porway led a 'DataDive' earlier this year in London, where data scientists collaborated with charities to offer analysis-driven solutions to recurring problems. A project using social media analysis to track public concerns in Indonesia and the US has already showed the value such methods hold for crisis response and social science research as a whole. The United Nations launched UN Global Pulse in 2009 with the primary aim of using best practices in the big data industry to enable the organisation to make faster and better informed responses to humanitarian crises. While more incremental gains would have taken place at any rate, such major strides have only been made achievable by the cloud computing services offered by - among others - Microsoft, Amazon and Teradata. Improvements in the speed and functionality of data collection, storage and analysis tools have lowered the cost of sequencing from almost £2bn to around £2,000 today, and cut the time it takes from over a decade to a week. The ability to map a person's genetic profile now allows doctors and scientists to predict a patient's susceptibility to certain diseases and other adverse conditions, and the major reductions in the time and cost of carrying out the procedure would not have been possible without big data. The mapping of the human genome is widely regarded as one of the most significant advances in the history of medical research. While a suspicious result is not direct evidence of fraud and cannot be used to incriminate an individual, it can help officials better target their auditing and other checks and procedures. Where privacy law allows, government departments can now cross-reference tax databases with other information such as vehicle registrations and overseas travel data to find individuals whose spending patterns and tax contributions do not add up.
Tax fraud is a growing concern for governments looking to cut their deficits, and big data is being used to increase the efficiency of fraud detection processes. While it can be easy to dismiss big data as overly corporate, irrelevant outside the business world, it is becoming increasingly clear that it can be - and is being - a force for good in the wider world. Some of these datasets, such as details of every one of a retailer's sales, will have a consistent format, with others stored as unstructured text.
0 kommentar(er)
