Business analytics

About: Business analytics is a research topic. Over the lifetime, 3593 publications have been published within this topic receiving 84601 citations. The topic is also known as: Business Analytics & business analytics.

Method and system for providing business intelligence based on user behavior

Abstract: Disclosed is a computer implemented method of providing business intelligence based on user behavior. The method may include a step of receiving a user identifier associated with the user from a requesting entity, such as a server computer. Further, the method may include a step of identifying an anonymous identifier corresponding to the user identifier. Additionally, the method may include a step of retrieving anonymous user behavior data based on the anonymous identifier. Furthermore, the method may include a step of transmitting the anonymous user behavior data to the requesting entity. Accordingly, the anonymous user behavior data may be used by the requesting entity to, for example, to enrich data, such as CRM data, of the user with the anonymous user behavior data.

Business intelligence for cross-process knowledge extraction at tourism destinations

Abstract: Decision-relevant data stemming from various business processes within tourism destinations (e.g. booking or customer feedback) are usually extensively available in electronic form. However, these data are not typically utilized for product optimization and decision support by tourism managers. Although methods of business intelligence and knowledge extraction are employed in many travel and tourism domains, current applications usually deal with different business processes separately, which lacks a cross-process analysis approach. This study proposes a novel approach for business intelligence-based cross-process knowledge extraction and decision support for tourism destinations. The approach consists of (a) a homogeneous and comprehensive data model that serves as the basis of a central data warehouse, (b) mechanisms for extracting data from heterogeneous sources and integrating these data into the homogeneous data structures of the data warehouse, and (c) analysis methods for identifying important relationships and patterns across different business processes, thereby bringing to light new knowledge. A prototype of the proposed concepts was implemented for the leading Swedish mountain destination Are, which demonstrates the effectiveness of the proposed business intelligence architecture and the gained business benefits for a tourism destination.

Big Data Analytics for Predictive Manufacturing Control - A Case Study from Process Industry

Abstract: Nowadays, companies are more than ever forced to dynamically adapt their business process executions to currently existing business situations in order to keep up with increasing market demands in global competition. Companies that are able to analyze the current state of their processes, forecast its most optimal progress and proactively control them based on reliable predictions will be a decisive step ahead competitors. The paper at hand exploits potentials through predictive analytics on big data aiming at event-based predictions and thereby enabling proactive control of business processes. In doing so, the paper particularly focus production processes in analytical process manufacturing industries and outlines-based on a case study at Saarstahl AG, a large German steel producing company-which production-related data is currently collected forming a potential foundation for accurate forecasts. However, without dedicated approaches of big data analytics, the sample company cannot utilize the potential of already available data for a proactive process control. Hence, the article forms a working and discussion basis for further research in big data analytics by proposing a general system architecture.