本文關(guān)鍵詞：論大數(shù)據(jù)分析的方法論意義　出處：《武漢科技大學(xué)》2015年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 大數(shù)據(jù) 大數(shù)據(jù)分析 方法論 局限性

【摘要】：數(shù)據(jù)科學(xué)的發(fā)展經(jīng)歷了數(shù)據(jù)的產(chǎn)生、科學(xué)數(shù)據(jù)的形成和大數(shù)據(jù)的誕生三個(gè)階段。三個(gè)階段的不斷發(fā)展改變了也加深了人們用數(shù)據(jù)看世界的觀念。隨著現(xiàn)代測(cè)量技術(shù)和智能設(shè)備的發(fā)展，數(shù)據(jù)的形式由傳統(tǒng)單一的結(jié)構(gòu)化數(shù)據(jù)演變?yōu)橛山Y(jié)構(gòu)化數(shù)據(jù)、半結(jié)構(gòu)化數(shù)據(jù)和非結(jié)構(gòu)化數(shù)據(jù)組成的復(fù)雜的數(shù)據(jù)形式。而互聯(lián)網(wǎng)、移動(dòng)互聯(lián)網(wǎng)的快速發(fā)展給了人們以分享這些數(shù)據(jù)的平臺(tái)，由此產(chǎn)生的海量數(shù)據(jù)被人們發(fā)現(xiàn)和利用，就產(chǎn)生了新型的大數(shù)據(jù)概念。大數(shù)據(jù)分析從技術(shù)手段上采用了最新的數(shù)據(jù)分析模型，通過(guò)數(shù)據(jù)之間特有的相關(guān)關(guān)系可以產(chǎn)生出許多有關(guān)聯(lián)、有價(jià)值的結(jié)論。 大數(shù)據(jù)分析在許多領(lǐng)域發(fā)揮了巨大的作用。在商業(yè)領(lǐng)域，，可收集的數(shù)據(jù)量非常巨大，不管是消費(fèi)者的直接的消費(fèi)數(shù)據(jù)，還是日常生活數(shù)據(jù)都可以被收集，經(jīng)過(guò)對(duì)收集來(lái)的海量數(shù)據(jù)進(jìn)行相關(guān)性分析之后，可以讓營(yíng)銷者實(shí)現(xiàn)精準(zhǔn)營(yíng)銷，增加成交量；在科學(xué)領(lǐng)域，比如海洋科學(xué)、生物科學(xué)、醫(yī)療健康科學(xué)以及天文學(xué)領(lǐng)域，由于歷史積累的數(shù)據(jù)量本來(lái)就大，加上現(xiàn)在的先進(jìn)技術(shù)產(chǎn)生的數(shù)據(jù)，導(dǎo)致數(shù)據(jù)量更是無(wú)比巨大，科學(xué)家通過(guò)大數(shù)據(jù)分析，可能會(huì)在這些海量數(shù)據(jù)基礎(chǔ)上形成數(shù)據(jù)密集型的科學(xué)發(fā)現(xiàn)及第四范式。在其他能產(chǎn)生大量數(shù)據(jù)的領(lǐng)域，大數(shù)據(jù)分析技術(shù)都能產(chǎn)生較大的效用。 從理論上說(shuō)，大數(shù)據(jù)技術(shù)與傳統(tǒng)的數(shù)據(jù)分析技術(shù)的根據(jù)基本一樣。傳統(tǒng)數(shù)據(jù)分析技術(shù)所具有的弊端，大數(shù)據(jù)同樣可能有。尤其是在數(shù)據(jù)源和數(shù)據(jù)的完整性方面，大數(shù)據(jù)分析技術(shù)的局限性是非常明顯的。因?yàn)楹Ａ康臄?shù)據(jù)并不能彼此保證每個(gè)數(shù)據(jù)都是真實(shí)可靠的，而且所謂海量數(shù)據(jù)也只是相對(duì)的大量，并不是有關(guān)方面的全部數(shù)據(jù)。所以，通過(guò)大數(shù)據(jù)分析獲得的結(jié)論可能具有更大的更多的實(shí)用價(jià)值，但并不必然為真。而且大數(shù)據(jù)分析對(duì)相關(guān)人群的隱私權(quán)可能造成某種程度的侵害。因此，在應(yīng)用大數(shù)據(jù)技術(shù)時(shí)應(yīng)科學(xué)合理，不可濫用。
[Abstract]:The development of data science has experienced the generation of data. The formation of scientific data and the birth of big data. The development of the three stages has changed and deepened the concept of people to see the world with data. With the development of modern measurement technology and intelligent equipment. The form of data changes from traditional single structured data to complex data form composed of structured data, semi-structured data and unstructured data. The rapid development of mobile Internet has given people a platform to share these data, and the resulting massive data has been discovered and utilized. Big data analysis adopts the latest data analysis model from the technical means, and through the special correlation relationship between the data, it can produce many relevant and valuable conclusions. Big data analysis has played a significant role in many areas. In business, the amount of data that can be collected is very large, whether it is consumer direct consumption data or daily life data can be collected. After the correlation analysis of the massive data collected, the marketers can achieve accurate marketing and increase the turnover. In the fields of science, such as marine science, biological science, medical and health sciences, and astronomy, the amount of data accumulated by history is already large, coupled with data generated by modern advanced technologies. Resulting in a huge amount of data, scientists through big data analysis, on the basis of these massive data may form a data-intensive scientific discovery and fourth paradigm, in other areas that can produce large amounts of data. Big data analysis technology can produce greater utility. In theory, the big data technology is basically the same as the traditional data analysis technology. The traditional data analysis technology has its drawbacks. Big data may also be. Especially in terms of data sources and data integrity, big data analysis technology limitations are very obvious, because the huge amount of data can not guarantee that every data is true and reliable. And the so-called massive data is only relatively large, not all the relevant data. Therefore, the conclusions obtained through big data analysis may have more practical value. But it is not necessarily true. And big data's analysis of the privacy of the people concerned may cause a certain degree of infringement. Therefore, the application of big data technology should be scientific and reasonable, can not be abused.
【學(xué)位授予單位】：武漢科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：TP311.13

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 紀(jì)宏,劉揚(yáng);論統(tǒng)計(jì)思想對(duì)于真理檢驗(yàn)的哲學(xué)意義(下)[J];北京統(tǒng)計(jì);1999年02期

2 馬建光;姜巍;;大數(shù)據(jù)的概念、特征及其應(yīng)用[J];國(guó)防科技;2013年02期

3 倪光南;;大數(shù)據(jù)的發(fā)展及應(yīng)用[J];信息技術(shù)與標(biāo)準(zhǔn)化;2013年09期

4 易歡歡;;互聯(lián)網(wǎng)金融發(fā)展與IT技術(shù)支撐[J];銀行家;2014年01期

5 李欣;劉萬(wàn)軍;;回歸分析數(shù)據(jù)挖掘技術(shù)[J];海軍航空工程學(xué)院學(xué)報(bào);2006年03期

6 王珊;王會(huì)舉;覃雄派;周p

本文編號(hào)：1384843