Yun Zhang
ABSTRACT
Data analysis process typically starts in an exploration phase, where the goal is to gain an understanding of the underlying data. In this phase, analysts make multiple queries and expect answers from the data services. Existing data services do not meet the needs for online data exploration in practice. Some services only support the data analysts to pull the whole dataset before analysis. Others allow analysts to make one-off queries and do not provide any guidance for exploring data. In this paper, we address these limitations of data services by proposing the Data Exploration as a Service (DEaaS) approach. Our RESTful service architecture and resource design provide explicit support for interactive data exploration. In addition, we use historical query information and predefined analytics semantics based on a multidimensional data model to recommend resources to analysts and guide them through the exploration process. We evaluate DEaaS using data exploration processes on both synthetic and real-life datasets. The experimental results show that our solution adapts to different data sources and the proposed resource navigation approach can make DEaaS outperform existing data services in data exploration.
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Index Terms
- A RESTful architecture for data exploration as a service
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