Banner Default Image

Data

​Big data primarily refers to data sets that are too large or complex to be dealt with by traditional data-processing application software. Data with many entries (rows) offer greater statistical power, while data with higher complexity (more attributes or columns) may lead to a higher false discovery rate.[2] Though used sometimes loosely partly because of a lack of formal definition, the interpretation that seems to best describe big data is the one associated with large body of information that we could not comprehend when used only in smaller amounts.[3]

Big data analysis challenges include capturing data, data storage, data analysis, search, sharing, transfer, visualization, querying, updating, information privacy, and data source. Big data was originally associated with three key concepts: volume, variety, and velocity.[4] The analysis of big data presents challenges in sampling, and thus previously allowing for only observations and sampling. Thus a fourth concept, veracity, refers to the quality or insightfulness of the data. Without sufficient investment in expertise for big data veracity, then the volume and variety of data can produce costs and risks that exceed an organization's capacity to create and capture value from big data.[5]

Current usage of the term big data tends to refer to the use of predictive analytics, user behavior analytics, or certain other advanced data analytics methods that extract value from big data, and seldom to a particular size of data set. "There is little doubt that the quantities of data now available are indeed large, but that's not the most relevant characteristic of this new data ecosystem."[6] Analysis of data sets can find new correlations to "spot business trends, prevent diseases, combat crime and so on".[7] Scientists, business executives, medical practitioners, advertising and governments alike regularly meet difficulties with large data-sets in areas including Internet searches, fintech, healthcare analytics, geographic information systems, urban informatics, and business informatics. Scientists encounter limitations in e-Science work, including meteorology, genomics,[8] connectomics, complex physics simulations, biology, and environmental research.[9]

The size and number of available data sets have grown rapidly as data is collected by devices such as mobile devices, cheap and numerous information-sensing Internet of things devices, aerial (remote sensing), software logs, cameras, microphones, radio-frequency identification (RFID) readers and wireless sensor networks.[10][11] The world's technological per-capita capacity to store information has roughly doubled every 40 months since the 1980s;[12] as of 2012, every day 2.5 exabytes (2.5×260 bytes) of data are generated.[13] Based on an IDC report prediction, the global data volume was predicted to grow exponentially from 4.4 zettabytes to 44 zettabytes between 2013 and 2020. By 2025, IDC predicts there will be 163 zettabytes of data.[14] According to IDC, global spending on big data and business analytics (BDA) solutions is estimated to reach $215.7 billion in 2021.[15][16] While Statista report, the global big data market is forecasted to grow to $103 billion by 2027.[17] In 2011 McKinsey & Company reported, if US healthcare were to use big data creatively and effectively to drive efficiency and quality, the sector could create more than $300 billion in value every year.[18] In the developed economies of Europe, government administrators could save more than €100 billion ($149 billion) in operational efficiency improvements alone by using big data.[18] And users of services enabled by personal-location data could capture $600 billion in consumer surplus.[18] One question for large enterprises is determining who should own big-data initiatives that affect the entire organization.[19]

Relational database management systems and desktop statistical software packages used to visualize data often have difficulty processing and analyzing big data. The processing and analysis of big data may require "massively parallel software running on tens, hundreds, or even thousands of servers".[20] What qualifies as "big data" varies depending on the capabilities of those analyzing it and their tools. Furthermore, expanding capabilities make big data a moving target. "For some organizations, facing hundreds of gigabytes of data for the first time may trigger a need to reconsider data management options. For others, it may take tens or hundreds of terabytes before data size becomes a significant consideration."[21]

​London is the capital and largest city of England and the United Kingdom. It stands on the River Thames in south-east England at the head of a 50-mile (80 km) estuary down to the North Sea, and has been a major settlement for two millennia.[9] The City of London, its ancient core and financial centre, was founded by the Romans as Londinium and retains boundaries close to its medieval ones.[note 1][10] Since the 19th century,[11] "London" has also referred to the metropolis around this core, historically split between the counties of Middlesex, Essex, Surrey, Kent, and Hertfordshire,[12] which largely comprises Greater London,[13] governed by the Greater London Authority.[note 2][14] The City of Westminster, to the west of the City of London, has for centuries held the national government and parliament.

​

London, as one of the world's global cities,[15] exerts strong influence on its arts, commerce, education, entertainment, fashion, finance, health care, media, tourism, and communications,[16] and therefore has sometimes been called the capital of the world.[17][18][19] Its GDP (€801.66 billion in 2017) makes it the biggest urban economy in Europe,[20] and it is one of the major financial centres in the world. In 2019 it had the second-highest number of ultra high-net-worth individuals in Europe after Paris[21] and the second-highest number of billionaires of any city in Europe after Moscow.[22] With Europe's largest concentration of higher education institutions,[23] it includes Imperial College London in natural and applied sciences, the London School of Economics in social sciences, and the comprehensive University College London.[24] The city is home to the most 5-star hotels of any city in the world.[25] In 2012, London became the first city to host three Summer Olympic Games.[26]

​

London's diverse cultures mean over 300 languages are spoken.[27] The mid-2018 population of Greater London of about 9 million[5] made it Europe's third-most populous city.[28] It accounts for 13.4 per cent of the UK population.[29] Greater London Built-up Area is the fourth-most populous in Europe, after Istanbul, Moscow and Paris, with 9,787,426 inhabitants at the 2011 census.[30][31] The London metropolitan area is the third-most populous in Europe after Istanbul's and Moscow's, with 14,040,163 inhabitants in 2016.[note 3][4][32]

​

London has four World Heritage Sites: the Tower of London; Kew Gardens; the combined Palace of Westminster, Westminster Abbey, and St Margaret's Church; and also the historic settlement in Greenwich, where the Royal Observatory, Greenwich defines the Prime Meridian (0° longitude) and Greenwich Mean Time.[33] Other landmarks include Buckingham Palace, the London Eye, Piccadilly Circus, St Paul's Cathedral, Tower Bridge and Trafalgar Square. It has numerous museums, galleries, libraries and sporting venues, including the British Museum, National Gallery, Natural History Museum, Tate Modern, British Library and West End theatres.[34] The London Underground is the oldest rapid transit system in the world.