Seesoft-A Tool for Visualizing Line Oriented Software Statistics
IEEE Transactions on Software Engineering - Special issue on software measurement principles, techniques, and environments
Fast subsequence matching in time-series databases
SIGMOD '94 Proceedings of the 1994 ACM SIGMOD international conference on Management of data
The need for metrics in visual information analysis
NPIV '97 Proceedings of the 1997 workshop on New paradigms in information visualization and manipulation
Clustering techniques for large data sets—from the past to the future
KDD '99 Tutorial notes of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Mining asynchronous periodic patterns in time series data
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Drawing graphs: methods and models
Drawing graphs: methods and models
XmdvTool: visual interactive data exploration and trend discovery of high-dimensional data sets
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Automated SLA Monitoring for Web Services
DSOM '02 Proceedings of the 13th IFIP/IEEE International Workshop on Distributed Systems: Operations and Management: Management Technologies for E-Commerce and E-Business Applications
Fast Similarity Search in the Presence of Noise, Scaling, and Translation in Time-Series Databases
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Similarity Clustering of Dimensions for an Enhanced Visualization of Multidimensional Data
INFOVIS '98 Proceedings of the 1998 IEEE Symposium on Information Visualization
Using extended feature objects for partial similarity retrieval
The VLDB Journal — The International Journal on Very Large Data Bases
Efficient Mining of Partial Periodic Patterns in Time Series Database
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
Managing Software with New Visual Representations
INFOVIS '97 Proceedings of the 1997 IEEE Symposium on Information Visualization (InfoVis '97)
A Java-Based Visual Mining Infrastructure and Applications
INFOVIS '99 Proceedings of the 1999 IEEE Symposium on Information Visualization
Parallel coordinates: a tool for visualizing multi-dimensional geometry
VIS '90 Proceedings of the 1st conference on Visualization '90
INFOVIS '05 Proceedings of the Proceedings of the 2005 IEEE Symposium on Information Visualization
VisBiz: a business process visualization case study
EUROVIS'05 Proceedings of the Seventh Joint Eurographics / IEEE VGTC conference on Visualization
The spatial-perceptual design space: a new comprehension for data visualization
Information Visualization
Designing dashboards for managing model lifecycle
Proceedings of the 2nd ACM Symposium on Computer Human Interaction for Management of Information Technology
BP-Ex: a uniform query engine for business process execution traces
Proceedings of the 13th International Conference on Extending Database Technology
Multidimensional data modeling for business process analysis
ER'07 Proceedings of the 26th international conference on Conceptual modeling
Modeling decisional knowledge with the help of data quality information
CDVE'11 Proceedings of the 8th international conference on Cooperative design, visualization, and engineering
OLAP technology for business process intelligence: challenges and solutions
DaWaK'07 Proceedings of the 9th international conference on Data Warehousing and Knowledge Discovery
Hi-index | 0.00 |
Business operations involve many factors and relationships and are modeled as complex business process workflows. The execution of these business processes generates vast volumes of complex data. The operational data are instances of the process flow, taking different paths through the process. The goal is to use the complex information to analyze and improve operations and to optimize the process flow. In this paper, we introduce a new visualization technique, called Vislmpact that turns raw operational business data into valuable information. Vislmpact reduces data complexity by analyzing operational data and abstracting the most critical factors, called impact factors, which influence business operations. The analysis may identify single nodes of the business flow graph as important factors but it may also determine aggregations of nodes to be important. Moreover, the analysis may find that single nodes have certain data values associated with them which have an influence on some business metrics or resource usage parameters. The impact factors are presented as nodes in a symmetric circular graph, providing insight into core business operations and relationships. A cause-effect mechanism is built in to determine 'good' and 'bad' operational behavior and to take action accordingly. We have applied Vislmpact to real-world applications, fraud analysis and service contract analysis, to show the power of Vislmpact for finding relationships among the most important impact factors and for immediate identification of anomalies. The Vislmpact system provides a highly interactive interface including drilldown capabilities down to transaction levels to allow multilevel views of business dynamics.