Titlebook: Measuring the Data Universe; Data Integration Usi Reinhold Stahl,Patricia Staab Book 2018 Springer International Publishing AG, part of Spr

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Introducing Standards Successfullying of the content. Here, a . provides for order and serves as a base for the definition of a ...The use of modern information technology (IT) cannot replace a sophisticated data and process model suitable for daily use. First there has to be an intelligent concept, then its realisation on an IT pla

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搬運(yùn)工

Contribution of the Statistics Standard SDMXplaced numerous individual agreements and enabled the development of so-called ...But the real potential of SDMX lies in its use as a classification system for any—and not only—financial and economic data. Many institutions use SDMX for data collection, data provision and Internet publishing. A real

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The Main Elements of SDMXirst introduced. Starting with the basic elements needed to define a data structure, we then gradually add the surrounding elements, such as those used to describe a data set, build a data exchange process, or manage topic areas, actors and processes..The conceptual world of SDMX is holistic enough

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Working with SDMXucts based on it have been self-developed by statistical institutions, and are therefore proprietary. However, there is a fair amount of open-source software provided by the SDMX community free of charge, which can be very helpful to those approaching the subject..These tools have a very different d

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SDMX as a Key Success Factor for Data Integration different national business phenomena and transferring the harmonised data sets via a file-based data exchange process into a uniform database. This was achieved with SDMX (Statistical Data and Metadata Exchange), but SDMX is much more. It is a non-technical model to classify any data world and thu

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r shop in a single echelon repairable multi-item spare parts supply system. The repair shop usually consists of several servers with different skill sets. Once a failure occurs in the system, the failed part is queued to be served by a suitable server that has the required skill. We model the repair

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Reinhold Stahl,Patricia Staab’ inventory levels are mutually not observable. In this paper, we study stochastic dynamic pricing models in a finite horizon duopoly model with partial information. To be able to derive effective pricing strategies when the competitor’s inventory level is not observable, we use a Hidden Markov Mode