Author: Nick Larsen

Nick Larsen, a Managing Partner at iOLAP, joined the company in 2005 and has extensive experience in designing, developing and managing large-scale Business Intelligence and Systems Integration projects. Nick has been the lead on many complex projects. As the Director of Professional Services, he is also responsible for resource and practice development and staffing/placement. He works with other iOLAP senior management to establish and lead strategic direction and the processes and methodologies of its professional services organization. Nick’s technical experience includes data modeling, technical architecture, data architecture, project management, and system integration. He has worked with multiple BI platforms including MicroStrategy, SAP BusinessObjects, Cognos, OBIEE, Yellowfin BI, Domo, and Tableau. Nick’s database expertise includes Netezza, Oracle, SQL Server, and Teradata. Nick received his BS in Business Computer Information Systems at the University of North Texas in 2004.

The Commoditization of the Data Model

The dimensional model is a thing of beauty when it is done right. It is designed independently of vendor and architecture. It is built with fact tables for every process, conformed dimensions, hierarchies, slowly changing dimensions, bridges, aggregates and so on. It is a work of art you print on a plotter and hang on your office wall for business users to gaze upon in total awe. It is the map you use to trace data lineage and figure out join paths. It is the reference guide for enhancement impact analysis.

Business Requirements: Not One Size Fits All

The total cost of operations (TCO) of Business Intelligence (BI) systems is often measured in three categories: time-to-completion of projects, on-budget completion of projects, and cost per user of BI applications. There is a key process in every project that impacts all three categories: Business Requirements Engineering.

An effective requirements methodology ensures that project scope is clearly understood and costs accurately estimated. At the same time, when we deliver what users want, usage and adoption of the solution increase the user base. Why then do so many programs not take a closer look and the effectiveness of their approach to this key part of the process?