Das Data-Mining-Konzept

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Data-driven modelling of the functional level in model-based systems engineering – Optimization of module scopes in modular development

The modelling of the functional level of technical systems can be supported by the analysis of machine usage data. By creating an understanding of the actual use of provided functions of offered machine configurations, the definition of module scopes in modular development can be optimized. Characteristics of specific machine usage can be assigned to physical elements using model-based systems engineering. Analyses on a purely functional system level can thus be placed in context with each other via the connection to physical elements. Consequently, critical elements in the system design can be systematically uncovered

Cluster Analysis of Smart Metering Data - An Implementation in Practice

The introduction of smart meter technology is a great challenge for the German energy industry. It requires not only large investments in the communication and metering infrastructure, but also a redesign of traditional business processes. The newly incurring costs cannot be fully passed on to the end customers. One option to counterbalance these expenses is to exploit the newly generated smart metering data for the creation of new services and improved processes. For instance, performing a cluster analysis of smart metering data focused on the customers’ time-based consumption behavior allows for a detailed customer segmentation. In the article we present a cluster analysis performed on real-world consumption data from a smart meter project conducted by a German regional utilities company. We show how to integrate a cluster analysis approach into a business intelligence environment and evaluate this artifact as defined by design science. We discuss the results of the cluster analysis and highlight options to apply them to segment-specific tariff design

On-Line Analytical Processing (OLAP) : Entscheidungsunterstützung von Führungskräften durch mehrdimensionale Datenbanksysteme

Seit einigen Jahren wird die Eignung von mehrdimensionalen Datenbanksystemen (OLAP) für die Analyseanforderungen von Führungskräften diskutiert. In dem Beitrag wird das OLAP-Konzept vorgestellt und im Hinblick auf die Unterstützung von Führungsentscheidungen untersucht

DESCRIPTIVE ATTRIBUTES OF ANALYSIS USE CASES IN THE DATA-DRIVEN VALIDATION OF ELEMENTS IN THE SYSTEM OF OBJECTIVES

Usage data of reference systems can be analyzed in the development process for the validation of system elements. The process model for data-driven validation of elements in the system of objectives aids developers in performing such data analyses. The conducted studies show that the basis for an efficient analysis process is a common understanding of the system and the goal of the analysis. Therefore, a template was derived over the course of case studies describing the elements in the system of objectives. The template covers the three descriptive dimensions general information, technical system and data. It allows a comprehensive description of analysis use cases. On average it takes 11 minutes for developers to aggregate all necessary information and consequently fill out the template. An A/B-Test confirmed the comprehensibility and applicability of the template even for developers of different domain knowledge. Through its contribution to a sustainable knowledge management the template provides an added value for the developers for conducting analysis

SUPPORT OF MANAGERIAL DECISION MAKING BY TRANSDUCTIVE LEARNING

Transductive inference has been introduced as a novelparadigm towards building predictive classi¯cation modelsfrom empirical data. Such models are routinely employedto support decision making in, e.g., marketing, risk manage-ment and manufacturing. To that end, the characteristics ofthe new philosophy are reviewed and their implications fortypical decision problems are examined. The paper\u27s objec-tive is to explore the potential of transductive learning forcorporate planning. The analysis reveals two main factorsthat govern the applicability of transduction in business set-tings, decision scope and urgency. In a similar fashion, twomajor drivers for its e®ectiveness are identi¯ed and empir-ical experiments are undertaken to con¯rm their in°uence.The results evidence that transductive classi¯ers are wellsuperior to their inductive counterparts if their speci¯c ap-plication requirements are ful¯lled

Personalisierung von EUS für Entscheidungsprozesse von Experten – Gestaltungspotenziale des Recognition-Primed Decision-Modells

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