Business intelligence data quality challenges and related best practice recommendations – A focus on Nigerian based SME's

Abstract

This paper aimed to accentuate concerns related to the quality of data that would typically constitute business intelligence for Small and  Medium Enterprises (SME’s) domiciled in Nigeria. Additionally, it proposed best practice recommendations to address the accentuated  concerns. To determine relevant data quality concerns, reference is made to generically acknowledged data quality dimensions. These  dimensions are widely regarded as aspects of data which necessitate assessments required to arrive at data quality judgements.  Particular attention is paid to data quality dimensions that pertain to structured data, given the invaluable role that structured data plays  in every profit-oriented establishment. To ensure that the determined data quality concerns are relevant to the experienced peculiarities  of Nigerian based SME’s a thorough literature review is conducted on data quality related challenges faced by Nigerian SME’s. The  findings from the literature review informs a systematic comparative analysis of twenty-five text files – which suggest best practice recommendations for addressing the related data quality challenges. The findings suggest that in order for the proposed best practice  recommendations to be adequately applied, Nigerian based SME’s must be sensitized on the importance of data capture, as well as pay  attention to quality aspects of any data captured. Furthermore, it is revealed that key stakeholders of Nigerian owned SME’s must  undergo capacity building exercises to improve their proficiency levels in the use of related digital tools required to capture and maintain  business intelligence related data at its optimum quality.