论文标题
数据分析的数据工程：问题的分类和案例研究
Data Engineering for Data Analytics: A Classification of the Issues, and Case Studies
论文作者
论文摘要
考虑数据分析师希望对给定数据集进行分析的情况。人们普遍认识到，分析师的大部分时间都将通过\ emph {数据工程}任务（例如获取，理解，清洁和准备数据）占用。在本文中，我们将此类任务的描述和分类分为高级组，即数据组织，数据质量和功能工程。我们还提供了四个数据集和示例分析，这些数据集表现出各种各样的问题，以帮助鼓励开发工具和技术，以帮助减轻这种负担，并将研究推向数据工程过程的自动化或半自动化。
Consider the situation where a data analyst wishes to carry out an analysis on a given dataset. It is widely recognized that most of the analyst's time will be taken up with \emph{data engineering} tasks such as acquiring, understanding, cleaning and preparing the data. In this paper we provide a description and classification of such tasks into high-levels groups, namely data organization, data quality and feature engineering. We also make available four datasets and example analyses that exhibit a wide variety of these problems, to help encourage the development of tools and techniques to help reduce this burden and push forward research towards the automation or semi-automation of the data engineering process.
