Application Scenarios and Practice of Data Science in the Context of Big Data

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Abstract

: With the development of the Internet, the era of BD (Big Data) is getting closer and closer. A country with mature BD has a future, and many enterprises cannot compete without BD. For example, BD can accurately position people's hobbies, the sales industry or service industry can use BD for precision marketing, and the development trend of BD includes data resource, data science, and the establishment of data alliances. Data science is a specialized discipline, a discipline born in the era of BD. It is at the intersection of statistics, machine learning and domain knowledge, and is an obvious interdisciplinary discipline. With the development of BD, data science must also develop with it. How data science develops and in which scenarios it can be applied remains to be studied. Through the research on BD and its development trend, and the theoretical research and analysis of data science, this paper aims to explore the specific application of data science, a new discipline, and practice it. Experiments have shown that applying data science to filtering spam and malware has a filtering rate of up to 95%. When applied to the sales industry, the predicted results are almost identical to the actual results. It has been confirmed that data science can collect, process, analyze data, and make predictive inferences. Data science can be applied to personalized content, navigation, and other scenarios that require prediction of results.
大数据背景下数据科学的应用场景与实践
随着互联网的发展,大数据时代越来越近。一个国家有成熟的BD就有未来,很多企业没有BD就无法竞争,比如BD可以精准定位人们的爱好,销售行业或者服务行业可以利用BD进行精准营销,BD的发展趋势包括数据资源、数据科学、建立数据联盟等。数据科学是一门专业学科,一门诞生于BD时代的学科,它处于统计学、机器学习和领域知识的交叉点,是一门明显的跨学科学科。随着BD的发展,数据科学也必须随之发展。数据科学如何发展,以及在哪些场景下可以应用,仍有待研究。本文旨在通过对BD及其发展趋势的研究,以及对数据科学的理论研究和分析,探索数据科学这一新兴学科的具体应用,并进行实践。实验表明,将数据科学应用于过滤垃圾邮件和恶意软件,过滤率高达95%。当应用到销售行业时,预测结果与实际结果几乎相同。已经证实,数据科学可以收集、处理、分析数据,并做出预测推断。数据科学可以应用于个性化内容、导航和其他需要预测结果的场景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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