53 lines
6.4 KiB
Markdown
53 lines
6.4 KiB
Markdown
---
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title: "Big data"
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chunk: 6/10
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source: "https://en.wikipedia.org/wiki/Big_data"
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category: "reference"
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tags: "science, encyclopedia"
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date_saved: "2026-05-05T09:53:36.506913+00:00"
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instance: "kb-cron"
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---
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=== Survey science ===
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Compared to survey-based data collection, big data has low cost per data point, applies analysis techniques via machine learning and data mining, and includes diverse and new data sources, e.g., registers, social media, apps, and other forms digital data. Since 2018, survey scientists have started to examine how big data and survey science can complement each other to allow researchers and practitioners to improve the production of statistics and its quality. There have been three Big Data Meets Survey Science (BigSurv) conferences in 2018, 2020 (virtual), 2023, and as of 2023 one conference forthcoming in 2025, a special issue in the Social Science Computer Review, a special issue in Journal of the Royal Statistical Society, and a special issue in EP J Data Science, and a book called Big Data Meets Social Sciences edited by Craig Hill and five other Fellows of the American Statistical Association. In 2021, the founding members of BigSurv received the Warren J. Mitofsky Innovators Award from the American Association for Public Opinion Research.
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=== Marketing ===
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Big data is notable in marketing due to the constant "datafication" of everyday consumers of the internet, in which all forms of data are tracked. The datafication of consumers can be defined as quantifying many of or all human behaviors for the purpose of marketing. The increasingly digital world of rapid datafication makes this idea relevant to marketing because the amount of data constantly grows exponentially. It is predicted to increase from 44 to 163 zettabytes within the span of five years. The size of big data can often be difficult to navigate for marketers. As a result, adopters of big data may find themselves at a disadvantage. Algorithmic findings can be difficult to achieve with such large datasets. Big data in marketing is a highly lucrative tool that can be used for large corporations, its value being as a result of the possibility of predicting significant trends, interests, or statistical outcomes in a consumer-based manner.
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There are three significant factors in the use of big data in marketing:
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Big data provides customer behavior pattern spotting for marketers, since all human actions are being quantified into readable numbers for marketers to analyze and use for their research. In addition, big data can also be seen as a customized product recommendation tool. Specifically, since big data is effective in analyzing customers' purchase behaviors and browsing patterns, this technology can assist companies in promoting specific personalized products to specific customers.
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Real-time market responsiveness is important for marketers because of the ability to shift marketing efforts and correct to current trends, which is helpful in maintaining relevance to consumers. This can supply corporations with the information necessary to predict the wants and needs of consumers in advance.
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Data-driven market ambidexterity are being highly fueled by big data. New models and algorithms are being developed to make significant predictions about certain economic and social situations.
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== Case studies ==
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=== Government ===
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==== China ====
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The Integrated Joint Operations Platform (IJOP, 一体化联合作战平台) is used by the government to monitor the population, particularly Uyghurs. Biometrics, including DNA samples, are gathered through a program of free physicals.
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By 2020, China plans to give all its citizens a personal "social credit" score based on how they behave. The Social Credit System, now being piloted in a number of Chinese cities, is considered a form of mass surveillance which uses big data analysis technology.
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==== India ====
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Big data analysis was tried out for the BJP to win the 2014 Indian General Election.
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The Indian government uses numerous techniques to ascertain how the Indian electorate is responding to government action, as well as ideas for policy augmentation.
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==== Israel ====
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Personalized diabetic treatments can be created through GlucoMe's big data solution.
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==== United Kingdom ====
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Examples of uses of big data in public services:
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Data on prescription drugs: by connecting origin, location and the time of each prescription, a research unit was able to exemplify and examine the considerable delay between the release of any given drug, and a UK-wide adaptation of the National Institute for Health and Care Excellence guidelines. This suggests that new or most up-to-date drugs take some time to filter through to the general patient.
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Joining up data: a local authority blended data about services, such as road gritting rotas, with services for people at risk, such as Meals on Wheels. The connection of data allowed the local authority to avoid any weather-related delay.
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==== United States ====
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In 2012, the Obama administration announced the Big Data Research and Development Initiative, to explore how big data could be used to address important problems faced by the government. The initiative is composed of 84 different big data programs spread across six departments.
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Big data analysis played a large role in Barack Obama's successful 2012 re-election campaign.
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The United States Federal Government owns four of the ten most powerful supercomputers in the world.
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The Utah Data Center has been constructed by the United States National Security Agency. When finished, the facility will be able to handle a large amount of information collected by the NSA over the Internet. The exact amount of storage space is unknown, but more recent sources claim it will be on the order of a few exabytes. This has posed security concerns regarding the anonymity of the data collected.
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=== Retail ===
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Walmart handles more than 1 million customer transactions every hour, which are imported into databases estimated to contain more than 2.5 petabytes (2560 terabytes) of data—the equivalent of 167 times the information contained in all the books in the US Library of Congress.
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Windermere Real Estate uses location information from nearly 100 million drivers to help new home buyers determine their typical drive times to and from work throughout various times of the day.
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FICO Card Detection System protects accounts worldwide.
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Omnichannel retailing leverages online big data to improve offline experiences. |