The Data Warehouse Lifecycle Toolkit: Expert Methods for Designing, Developing and Deploying Data Warehouses with CD Rom
Modeling Multidimensional Databases
ICDE '97 Proceedings of the Thirteenth International Conference on Data Engineering
Modeling Multidimensional Databases, Cubes and Cube Operations
SSDBM '98 Proceedings of the 10th International Conference on Scientific and Statistical Database Management
Data integration flows for business intelligence
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
QoX-driven ETL design: reducing the cost of ETL consulting engagements
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
Defining ETL worfklows using BPMN and BPEL
Proceedings of the ACM twelfth international workshop on Data warehousing and OLAP
Towards formal analysis of artifact-centric business process models
BPM'07 Proceedings of the 5th international conference on Business process management
Leveraging business process models for ETL design
ER'10 Proceedings of the 29th international conference on Conceptual modeling
GEM: requirement-driven generation of ETL and multidimensional conceptual designs
DaWaK'11 Proceedings of the 13th international conference on Data warehousing and knowledge discovery
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The design and implementation of an ETL (extract-transform-load) process for a data warehouse proceeds from a conceptual model to a logical model, and then a physical model and implementation. The conceptual model conveys at a high level the data sources and targets, and the transformation steps from sources to targets. The current state of the art is to express the conceptual model informally using text descriptions and diagrams. This makes the process of deriving a logical model time-consuming and error-prone. Our work is towards a system that covers the whole ETL lifecycle by injecting several layers of optimization and validation throughout the whole process starting with the business level objectives and ending with flow execution. In this paper, we focus on the ETL conceptual layer and present a solution that assists consultants in their task of defining the needs and requirements at the early stages of an integration project. We present a conceptual model for ETL based on hypercubes and hypercube operations. This is a formal model that captures the semantics of ETL at a high-level but that can also be machine-translated into a logical model for ETL. The use of hypercubes at the conceptual level renders a design that can be easily understood by business users and so reduces design and development time and produces a result that accurately captures service level agreements and business requirements.