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整合数据、工具和科学

Integrating Data, Tools and Science
课程网址: http://videolectures.net/ecmlpkdd2010_berthold_idts/  
主讲教师: Michael Berthold
开课单位: 康斯坦茨大学
开课时间: 2020-09-16
课程语种: 英语
中文简介:
多年来,众所周知的事实是,数据分析项目只花费一小部分时间进行实际分析。更多的时间用于收集、整合和准备分析数据。尽管如此,许多数据分析工具只关注分析部分。在本次演讲中,我们将介绍KNIME(一个开源集成和分析平台)背后的核心技术。除了提供全面的内置ETL、分析和可视化方法外,KNIME的开放API还促进了其他工具的集成。底层的模块化体系结构使分布在企业IT环境中的各种数据源实现了一致和透明的融合,同时集成了现有的遗留工具和其他数据处理和分析方法。我们将展示KNIME作为集成和分析主干成功部署的真实世界示例,以及如何使用KNIME快速部署新科学,例如同时分析和探索数据的新方法。我们还将花时间简要概述数据工作流的图形化、模块化表示方式如何使复杂的数据处理和分析过程得以记录、归档和传达。
课程简介: For years it has been a well-known fact that data analysis projects spend only a small fraction of time on actual analysis. Much more time is spent gathering, integrating and preparing the data for analysis. Still, many data analysis tools focus on the analytical parts only. In this talk we will present the core technology behind KNIME, an open source integration and analysis platform. In addition to offering comprehensive built-in ETL, analysis and visualization methods, KNIME's open API facilitates the integration of other tools. The underlying modular architecture enables a coherent and transparent fusion of the diverse data sources spread out over the corporate IT environment, while at the same time integrating existing legacy tools and other data processing and analysis methods. We will show real-world examples of KNIME being successfully deployed as an integration and analysis backbone and how it can be used to quickly deploy new science, e.g. new methods for the analysis and exploration of data at the same time. We will also take the time to provide a brief overview of how the graphical, modular representation of a data workflow enables complex data processing and analysis procedures to be documented, archived and communicated.
关 键 词: 数据分析; 数据整合; KNIME
课程来源: 视频讲座网
数据采集: 2021-05-27:liyy
最后编审: 2023-03-09:liyy
阅读次数: 49