Analytics-as-a-service workflow orchestration

分析即服务工作流程编排

• 批准号: 453459-2013
• 负责人: Martin, Patrick
• 金额: $ 5.03万
• 依托单位: Queen's University
• 依托单位国家: 加拿大
• 项目类别: Collaborative Research and Development Grants
• 财政年份: 2014
• 资助国家: 加拿大
• 起止时间: 2014-01-01 至 2015-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=555041
• 关键词: Analytics; service; workflow; orchestration

The explosion of data now available from both private and public data sources means analytics technologies that mine structured and unstructured data to derive insights to improve decision-making are receiving substantial attention. The traditional data analytics architecture consists of a data warehouse that consolidates data using data integration processes from several operational sources and provides querying, reporting, and analytical tools. Data integration is a batch process implemented by Extract-Transform-Load (ETL) tools. However, as organizations become more automated, real-time and data-driven, this architecture cannot satisfy the enterprises' need for real-time data analytics.

现在，来自私人和公共数据源的数据爆炸式增长，意味着挖掘结构化和非结构化数据以获得洞察力以改善决策的分析技术正在受到极大的关注。传统的数据分析架构由数据仓库组成，该数据仓库使用来自多个操作源的数据集成流程整合数据，并提供查询、报告和分析工具。数据集成是一个由提取-转换-加载（ETL）工具实现的批处理过程。然而，随着组织变得更加自动化，实时和数据驱动，这种架构无法满足企业对实时数据分析的需求。