Abstract
Business Analytics and Intelligence tools (BAI) are spreading across all industries. As the amount of business data exponentially grows everyday, it is critical to have appropriate tools that make it possible to consume and take profit of this digital universe. Even though BAI tools have positively evolved in this direction, meaningful and productive use of data still remains a major obstacle for most organizations. Of drowning in data, they have moved to drown in reports, dashboards and data summaries. We believe that BAI technologies should evolve towards a more holistic approach in which business users can focus on business concepts and questions, without wasting time in lower levels of cumbersome data manipulation. We propose the Business Analytics Architecture (BAA) as the infrastructure supporting ‘smart’ and enterprise BAI operations. It enables users to define the business concepts they want to focus on, as well as connecting them with data at storage level. Analytical and data-mining algorithms are intensively exploited, all guided by the ‘semantic layer’ previously depicted by business users. BAA integrating up-to-date data mining and artificial intelligence techniques as well as some well-known business practices such as Balanced Scorecard and Strategy Maps.
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Notes
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Enterprise Resource Planning, Material Resource Planning and Customer Relationship Management, respectively.
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Villegas-García, M.A., García Márquez, F.P., Pedregal Tercero, D.J. (2015). How Business Analytics Should Work. In: García Márquez, F., Lev, B. (eds) Advanced Business Analytics. Springer, Cham. https://doi.org/10.1007/978-3-319-11415-6_5
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DOI: https://doi.org/10.1007/978-3-319-11415-6_5
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