Data-Warehouse as a Dynamic Capability: Utility/Cost Foundations and Implications for Economically-Driven Design

IS design today is driven primarily by technical and functional requirements, and the economic implications for design are not yet well understood. This study argues that system design and architecture must reflect assessments of economic trade-offs besides satisfying technical/functional requirements. Modeling the economic performance structure behind IS design can highlight these trade-offs and help economically assess design alternatives. This study examines economics-driven design in the context of the Data Warehouse (DW). The DW environment is treated as a dynamic capability, providing the capacity for managing data resources and turning them into useful information products. These products contribute value when used for exploitative and/or explorative business processes. Recognizing possible uncertainties in usage, DW capacities are evaluated as real-option investments toward the development of a framework for modeling cost-utility effects of DW design decisions. This framework is used to evaluate important design scenarios along the layers of a DW stack architecture and optimize design outcomes accordingly

Boundary Interactions and Motors of Change in Requirements Elicitation: A Dynamic Perspective on Knowledge Sharing

The building of shared understanding between project stakeholders in the requirements elicitation phase is necessary for knowledge sharing and a key factor for successful information systems (IS) development. However, the processes that lead to shared understanding and successful knowledge sharing are still not well understood. We examine how stakeholders interact and use boundary objects during requirements elicitation in data warehouse development projects. We draw on Carlile’s (2004) framework for managing knowledge across boundaries and introduce the concept of brokering situations. Using the concept of brokering situations, we examine how shared understanding develops and knowledge is shared through the interplay of brokers, their individual knowledge, and boundary objects as well as through the alignment of project participants’ situation models. We contribute to the literature on knowledge sharing and requirements elicitation in three ways: by introducing the concept of brokering situations; by developing a theoretical framework – the boundary interaction framework – that provides an analytical perspective on the dynamics of knowledge sharing in requirements elicitation; and by applying the framework to show that both goal-driven (teleological) and conflict-driven (dialectical) motors of change explain process progress and the changes of brokers as well as boundary objects during the building of shared understanding

Using Ontologies for the Design of Data Warehouses

Obtaining an implementation of a data warehouse is a complex task that forces designers to acquire wide knowledge of the domain, thus requiring a high level of expertise and becoming it a prone-to-fail task. Based on our experience, we have detected a set of situations we have faced up with in real-world projects in which we believe that the use of ontologies will improve several aspects of the design of data warehouses. The aim of this article is to describe several shortcomings of current data warehouse design approaches and discuss the benefit of using ontologies to overcome them. This work is a starting point for discussing the convenience of using ontologies in data warehouse design.Comment: 15 pages, 2 figure

Requirements analysis method for extracting-transformation-loading (ETL) in data warehouse systems

The data warehouse (DW) system design involves several tasks such as defining the DW schemas and the ETL processes specifications, and these have been extensively studied and practiced for many years.The problems in heterogeneous data integration are still far from being resolved due to the complexity of ETL processes and the fundamental problems of data conflicts in information sharing environments.The understanding of an early phase of DW development is essential in properly tackling the complexity of ETL processes.The method to analyses the DW requirements from the abstract level (e.g. goal, sub-goal, stakeholder, dependency) toward the specification of ETL processes (e.g. extracting, filtering, conversion) are important in order to manage the complexity of the ETL processes design (e.g. semantic heterogeneity problems). However, current approaches that are based on existing software requirement approach still have limitations on translating the business semantics for DW requirements toward the ETL processes specifications.Moreover, the understanding of goal in the perspective of the organization and decision makers are important to ensure the semantic of DW requirements can be properly determined, organized, and implemented by the ETL processes. Therefore, the proposed method will utilize the ontology with goal-driven approach in analyzing the requirements of ETL processes