Optimization of parallel query execution plans in XPRS
Distributed and Parallel Databases - Selected papers from the first international conference on parallel and distributed information systems
The Data Warehouse Lifecycle Toolkit: Expert Methods for Designing, Developing and Deploying Data Warehouses with CD Rom
A survey of approaches to automatic schema matching
The VLDB Journal — The International Journal on Very Large Data Bases
iBOM: A Platform for Intelligent Business Operation Management
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
RPJ: producing fast join results on streams through rate-based optimization
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Clio grows up: from research prototype to industrial tool
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
State-Space Optimization of ETL Workflows
IEEE Transactions on Knowledge and Data Engineering
Progressive merge join: a generic and non-blocking sort-based join algorithm
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Deciding the physical implementation of ETL workflows
Proceedings of the ACM tenth international workshop on Data warehousing and OLAP
A generic solution for warehousing business process data
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Meshing Streaming Updates with Persistent Data in an Active Data Warehouse
IEEE Transactions on Knowledge and Data Engineering
Multidimensional content eXploration
Proceedings of the VLDB Endowment
Natural language reporting for ETL processes
Proceedings of the ACM 11th international workshop on Data warehousing and OLAP
RiTE: Providing On-Demand Data for Right-Time Data Warehousing
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
A metric definition, computation, and reporting model for business operation analysis
EDBT'06 Proceedings of the 10th international conference on Advances in Database Technology
Data integration flows for business intelligence
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
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Business processes drive the operations of an enterprise. In the past, the focus was primarily on business process design, modeling, and automation. Recently, enterprises have realized that they can benefit tremendously from analyzing the behavior of their business processes with the objective of optimizing or improving them. In our research, we address the problem of warehousing business process execution data so that we can analyze their behavior using the analytic and reporting tools that are available in data warehouse environments. We build upon our previous work that described the design and implementation of a generic process data warehouse for use with any business processes. In this paper, we show how to automate the population of the generic process warehouse by tracking business events from an application environment. Typically, the source data consists of event streams that indicate changes in the business process state (i.e., progression of the process). The target schema is designed to allow querying of task and process execution data. The core of our approach for processing progression data relies on the construction of generic templates that specify the semantics of the event streams extraction and the subsequent transformations that translate the underlying IT events into business data changes. Using this extensible template mechanism, we show how to automate the construction of mappings to populate the generic process warehouse using two-levels of mappings that are applied in two-phases. Interestingly, our approach of using ETL technology for warehousing process data can be seen the other way around. An arbitrary ETL process can be modeled as a business process. Hence, we describe the benefit of modeling ETL as a business process and illustrate how to use our approach to warehouse ETL execution data, and to monitor and analyze the progress of ETL processes. Finally, we discuss implementation issues.