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General Architectural Framework for Business Visual Analytics

2018; Springer Science+Business Media; Linguagem: Inglês

10.1007/978-3-319-94214-8_19

1865-1356

Yavor Dankov, Dimitar Birov,

Time Series Analysis and Forecasting

An incredible amount of data has constantly been generated. There is a gap between the abundance of data and the needs of users. At the same time a particular user needs not only a relevant part of the available data but (s)he needs higher-level (inferred) data in order to use this data in support of decision-making. Analytics comes to bridge that gap, by means of tools. Those tools link what the user needs to what is available as data; generate higher-level (inferred) data based on the raw data; provide visualization that is useful especially to users that have limited knowledge in mathematics and data science. The abundance of definitions that concern analytics as well as the numerous terms and concepts confuse users. Often different concepts are inconsistent with regard to each other. Inspired by this problem, the current paper: provides a systematic analysis featuring analytics in general and business analytics, in particular, developing this also from the perspective of visualization-related needs. We propose a layered business analytics architecture named General Architectural Framework for Business Visual Analytics. The framework presents the main interrelationships between the elements for designing and modeling Business Visual Analytics. We propose a conceptual definition that combines the semantics of the multiple recurring and overlapping definitions of analytics, named Business Visual Analytics (BVA). This is a new conceptual viewpoint mainly focused on the innovative data visualization techniques, business analytics capabilities and achieving business goals and performance. The paper is reporting research in progress and for this reason, further architectural developments and related validations are planned for further research.