Purpose

Data mining along with its varied technologies like numerical mining, textual mining, multimedia mining, web mining, sentiment analysis and big data mining proves itself as an emerging field and manifests itself in the form of different techniques such as information mining; big data mining; big data mining and Internet of Things (IoT); and educational data mining. This paper aims to discuss how these technologies and techniques are used to derive information and, eventually, knowledge from data.

Design/methodology/approach

An extensive review of literature on data mining and its allied techniques was carried to ascertain the emerging procedures and techniques in the domain of data mining. Clarivate Analytic’s Web of Science and Sciverse Scopus were explored to discover the extent of literature published on Data Mining and its varied facets. Literature was searched against various keywords such as data mining; information mining; big data; big data and IoT; and educational data mining. Further, the works citing the literature on data mining were also explored to visualize a broad gamut of emerging techniques about this growing field.

Findings

The study validates that knowledge discovery in databases has rendered data mining as an emerging field; the data present in these databases paves the way for data mining techniques and analytics. This paper provides a unique view about the usage of data, and logical patterns derived from it, how new procedures, algorithms and mining techniques are being continuously upgraded for their multipurpose use for the betterment of human life and experiences.

Practical implications

The paper highlights different aspects of data mining, its different technological approaches, and how these emerging data technologies are used to derive logical insights from data and make data more meaningful.

Originality/value

The paper tries to highlight the current trends and facets of data mining.

中文翻译：

---

探索数据挖掘：方面和新兴趋势

目的

数据挖掘以其数值挖掘、文本挖掘、多媒体挖掘、网络挖掘、情感分析和大数据挖掘等多种技术，证明了其作为一个新兴领域，并以信息挖掘等不同技术的形式表现出来；大数据挖掘；大数据挖掘和物联网（IoT）；和教育数据挖掘。本文旨在讨论如何使用这些技术和技巧从数据中获取信息，并最终从数据中获取知识。

设计/方法/方法

对数据挖掘及其相关技术的文献进行了广泛的审查，以确定数据挖掘领域的新兴程序和技术。探索了 Clarivate Analytic 的科学网络和 Sciverse Scopus，以发现有关数据挖掘及其各个方面的文献的范围。以数据挖掘等各种关键词检索文献；信息挖掘；大数据; 大数据和物联网；和教育数据挖掘。此外，还探索了引用数据挖掘文献的作品，以可视化有关这一不断发展的领域的各种新兴技术。

发现

该研究证实，数据库中的知识发现使数据挖掘成为一个新兴领域；这些数据库中存在的数据为数据挖掘技术和分析铺平了道路。本文提供了关于数据使用的独特观点，以及从中衍生的逻辑模式，新程序、算法和挖掘技术如何不断升级以实现其多用途，以改善人类生活和体验。

实际影响

本文重点介绍了数据挖掘的不同方面、其不同的技术方法，以及如何使用这些新兴的数据技术从数据中获得逻辑见解并使数据更有意义。

原创性/价值

本文试图突出数据挖掘的当前趋势和方面。