Titlebook: Business Intelligence for the Real-Time Enterprises; First International Christoph Bussler,Malu Castellanos,Sham Navathe Conference procee

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The Missing Public in U.S. Public Diplomacy, Such data sources include in-house applications (like CRM, ERP), partner databases (like loyalty card data from retailers), and syndicated data sources (like credit reports from Experian). However, different data sources represent the same semantic attributes in different ways. E.g., two XML schema

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The Missing Public in U.S. Public Diplomacy,erging” dynamically to respond to new opportunities. But these constituent businesses were not built in any standard way, and neither were their IT systems. An example in the industrial sector is the need to merge product and parts catalogs, and selectively share customer data. Companies that merge

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Fredrik Hacklin,David Klang,Pius Bascherare solutions such as supply chain management, logistics, and inventory control. Integration of automatic data acquisition with enterprise applications as well as potential to provide real-time analytic functionality is opening new avenues for business process automation. In this paper, we propose a

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Snezhanka Kazakova,Verolien Caubergherements we propose a Process Learning System (PLS) that is capable of learning business processes from a few observed traces and do this in a timeframe that is close to the actual time for completing the process. Unlike existing approaches PLS employs a rich process model that facilitates “guessing”

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Media and Convergence Management-wide business processes. BPMSs promise to facilitate automation, integration, and optimization of business processes in order to support decision making, increase operational efficiency, and lower the cost of doing business. In spite of the growing popularity, however, realization of the grand visi

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Convergence and Consumer Behavioroaded and both queries and updates can be finished quickly. However, this goal becomes fundamentally hard to achieve due to the high volume of queries and updates in real systems, especially in periods of flash crowds. In such cases, systems typically try to optimize for the average case, treating a

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https://doi.org/10.1007/978-3-030-35173-1The area of real-time business intelligence is ill defined in industry. In this extended abstract we highlight the practical requirements through the use of examples across several domains.