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Engineering the Black-Box Meta Model of Data Exploration

机译:设计数据探索的黑盒元模型

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With an increasing amount and diversity of available data, data exploration is becoming critical for many businesses to create insights for business innovation. From an analysis and design perspective, however, data exploration is still dominated by IT-oriented modeling concepts that make it difficult to engage business users because they are not used to think in terms of (even conceptual) data structures, but rather in terms of business questions, intended insights, decision context, information quality, etc. This study elaborates requirements for conceptualizing data exploration from a business perspective, discusses to what extent existing business-oriented conceptualizations fulfil such requirements, and consolidates promising modeling concepts into a meta model proposal that links purpose, context, domain knowledge, exploration history, business question, available data, user, decision, business insight, presentation and non-user stakeholder as key concepts. The meta model is demonstrated by instantiating it to conceptualize five exemplary data exploration use cases, and first evaluative evidence is presented. The paper closes with a discussion how to transform the proposed meta model into an innovative data exploration analysis and design tool.
机译:随着可用数据量的增加和多样性,数据探索对于许多企业创建业务创新见解变得至关重要。但是,从分析和设计的角度来看,数据探索仍然是由面向IT的建模概念主导的,这些概念使业务用户难以参与,因为他们不习惯于以(甚至是概念性的)数据结构来思考,而是以业务问题,预期的见解,决策环境,信息质量等。此研究从业务角度阐述了对数据探索进行概念化的要求,讨论了现有的面向业务的概念化在多大程度上满足了此类要求,并将有希望的建模概念整合到了元模型建议中它将目的,上下文,领域知识,探索历史,业务问题,可用数据,用户,决策,业务洞察力,演示文稿和非用户利益相关者联系在一起作为关键概念。通过实例化元模型以概念化五个示例性数据探索用例来演示该元模型,并提供第一份评估证据。本文最后讨论了如何将提出的元模型转换为创新的数据探索分析和设计工具。

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