The Data Warehouse Lifecycle Toolkit: Expert Methods for Designing, Developing and Deploying Data Warehouses with CD Rom
Systems Analysis and Design
A Method for Demand-Driven Information Requirements Analysis in Data Warehousing Projects
HICSS '03 Proceedings of the 36th Annual Hawaii International Conference on System Sciences (HICSS'03) - Track 8 - Volume 8
Data Warehouse Design: Modern Principles and Methodologies
Data Warehouse Design: Modern Principles and Methodologies
Strategic models for business intelligence
ER'11 Proceedings of the 30th international conference on Conceptual modeling
Business model ontologies in OLAP cubes
CAiSE'13 Proceedings of the 25th international conference on Advanced Information Systems Engineering
Monitoring and diagnosing indicators for business analytics
CASCON '13 Proceedings of the 2013 Conference of the Center for Advanced Studies on Collaborative Research
CASCON '13 Proceedings of the 2013 Conference of the Center for Advanced Studies on Collaborative Research
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Business Intelligence (BI) projects are long and painful endeavors that employ a variety of design methodologies, inspired mostly by software engineering and project management lifecycle models. In recent BI research, new design methodologies are emerging founded on conceptual business models that capture business objectives, strategies, and more. Their claim is that they facilitate the description of the problem-at-hand, its analysis towards a solution, and the implementation of that solution. The key question explored in this work is:Are such models actually useful to BI design practitioners? To answer this question, we conducted an in situ empirical evaluation based on an on-going BI project for a Toronto hospital. The lessons learned from the study include: confirmation that the BI implementation is well-supported by models founded on business concepts; evidence that these models enhance communication within the project team and business stakeholders; and, evidence that there is a need for business modeling to capture BI requirements and, from those, derive and implement BI designs.