High Quality Analytics with Poor Quality Data

Abstract

Poor data quality has often been cited as the single most common problem hindering the deployment of Business Intelligence (BI) solutions. This problem is compounded when analytics is performed in non-conventional BI areas such as forestry and silviculture. In this paper, we describe a methodology to perform BI analytics on data that was never collected to be used for this purpose. We show that data of such low and poor quality can be transformed and loaded into the data warehouse which is then used for high quality reporting.