Understanding the benefits of source data analytics towards BI design

Many companies start a data warehouse project without fully understanding their existing legacy systems, their architecture, company business processes, and the state of data within the systems. Much of the research that has been done within BI has consisted of different methodologies of development for the solution, (Kimball Model, ERD model), and very little to do with preparation or readiness (Fitriana, Eriyatno, & Djatna, 2011). Of the available packaged solutions on the market for BI, most are built to fit a larger audience, and specific company customizations either become costly or unavailable. Ultimately, the literature points towards understanding what systems are in place, what business processes exist or should exist, and what data will make up the "information" comprised within the BI systems dashboards. Through the Design Science Research method, this research aimed to define an autonomous method to "scan" database systems and determine data validity or data saturation, in effect to determine if companies/organizations BI or data warehouse development can benefit from a visual view of data saturation.