Building a Collaborative Data Analytics System: Opportunities and Challenges

IF 2.6 3区计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS

Proceedings of the Vldb Endowment Pub Date : 2023-08-01 DOI:10.14778/3611540.3611580

Zuozhi Wang, Chen Li

引用次数: 0

Abstract

Real-time collaboration has become increasingly important in various applications, from document creation to data analytics. Although collaboration features are prevalent in editing applications, they remain rare in data-analytics applications, where the need for collaboration is even more crucial. This tutorial aims to provide attendees with a comprehensive understanding of the challenges and design decisions associated with supporting real-time collaboration and user interactions in data analytics systems. We will discuss popular conflict resolution technologies, the unique challenges of facilitating collaborative experiences during the workflow construction and execution phases, and the complexities of supporting responsive user interactions during job execution.

查看原文本刊更多论文

构建协作数据分析系统:机遇与挑战

从文档创建到数据分析，实时协作在各种应用程序中变得越来越重要。尽管协作特性在编辑应用程序中很普遍，但在数据分析应用程序中仍然很少，在数据分析应用程序中，协作需求更为重要。本教程旨在为与会者提供与支持数据分析系统中的实时协作和用户交互相关的挑战和设计决策的全面理解。我们将讨论流行的冲突解决技术、在工作流构建和执行阶段促进协作体验的独特挑战，以及在作业执行期间支持响应式用户交互的复杂性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Proceedings of the Vldb Endowment Computer Science-General Computer Science

CiteScore

7.70

自引率

0.00%

发文量

期刊介绍： The Proceedings of the VLDB (PVLDB) welcomes original research papers on a broad range of research topics related to all aspects of data management, where systems issues play a significant role, such as data management system technology and information management infrastructures, including their very large scale of experimentation, novel architectures, and demanding applications as well as their underpinning theory. The scope of a submission for PVLDB is also described by the subject areas given below. Moreover, the scope of PVLDB is restricted to scientific areas that are covered by the combined expertise on the submission’s topic of the journal’s editorial board. Finally, the submission’s contributions should build on work already published in data management outlets, e.g., PVLDB, VLDBJ, ACM SIGMOD, IEEE ICDE, EDBT, ACM TODS, IEEE TKDE, and go beyond a syntactic citation.