Date of Award

Fall 11-25-2013

Document Type

Dissertation

Degree Name

Doctor of Science in Information Systems

Department

Business and Information Systems

First Advisor

Surendra Sarnikar

Second Advisor

Maureen Murphy

Third Advisor

Amit Deokar

Abstract

Organizations are continually accumulating large amounts of business data, as an increasing number of business processes are being conducted electronically. Analyzing these large data sets is often referred to as the “Big Data” problem because of the complexity and distributed nature of the data. While there is an abundance of business data available to business users for analysis, it is not being used due to lack of Business Intelligence (BI) Tools’ capability and a growing backlog of requests to Enterprise IT departments for new and modified data models to support continuously evolving reporting and analysis requirements. In addition, current processes for the design of data models predominantly relies on a sequential and phased approach from requirement collection to data model development; therefore; business analysts often do not get to see the impact of the changes until a prototype is created. This process is often time-consuming and can further exacerbate the large backlogs of requests for new and modified data models at IT departments. This dissertation addresses the above problem by proposing a collaboration-based tool for use by business users and database developers that can reduce communication gaps, help with the different views of data representation between the different disciplines, and lead to faster development of more comprehensive data models for addressing underlying business needs. Using a design science approach, an IT Artifact is developed with a basis in Inter-disciplinary Communication Medium (ICM) and Data/Frame Theory. The potential impact of this process is a more accurate data model that is delivered more quickly, because less rework would be required and less scope creep; thus, the business can better develop its requirements in the early conceptual design phase. This design science research resulted in the development of a model and instantiation of a Multi Perspective Inter-Disciplinary Communication System for Business Intelligence System Design. This dissertation research describes the theory-driven design of the system, the system implementation and results from the user study of a novel way to create more comprehensive and accurate data models for BI and decision support.

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