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Towards a better understanding of the influence of Business Intelligence (BI) Maturity Level on the relationship between BI Success and the BI Capabilities, with a focus on Data Quality as a BI Capability

Lafferty, David (2019) Towards a better understanding of the influence of Business Intelligence (BI) Maturity Level on the relationship between BI Success and the BI Capabilities, with a focus on Data Quality as a BI Capability. Masters thesis, Dublin, National College of Ireland.

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Abstract

Purpose: The purpose of this study is to extend the research carried out in previous research related to BI system Success factors to examine the relationship between BI Success and BI Data Quality capabilities using a quantitative approach. This dissertation also examines the strength of the relationship between BI Success and BI Data Quality capabilities.

Structure: This study adopted a quantitative approach to research. Respondents were questioned through an online, open and closed question survey to gather data regarding their satisfaction with their BI system, the strengths of the BI Quality capabilities and questions designed to enable calculation of their organisations BI Maturity level.

Originality/Value: It is becoming ever more important for Business to make best use of the vast amount of data that is being created within organisations to support their decision-making processes. As data becomes every more complex, the need to have a BI system does supports this becomes every more important. Despite the importance of BI Systems for business there is still a very high failure rate of BI implementation and adoption. There is currently not enough research in the area of BI success for a framework to be established to guide organisations towards BI system implementation.

Concluding Statement: Results validate previous research results that show the strong correlation between BI Success and BI quality Capabilities. Results indicate that organisations with Lower Maturity Levels have less reliance on Data Reliability and Data Source Quality then those with higher Maturity Levels, but that Data Quality is very important regardless of level.

Item Type: Thesis (Masters)
Subjects: Q Science > QA Mathematics > Electronic computers. Computer science > Computer Systems > Information Storage and Retrieval Systems > Management Information Systems
T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science > Computer Systems > Information Storage and Retrieval Systems > Management Information Systems

H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management > Strategic Management
Divisions: School of Business > Master of Science in Management
Depositing User: CAOIMHE NI MHAICIN
Date Deposited: 23 Oct 2019 10:07
Last Modified: 23 Oct 2019 10:07
URI: http://trap.ncirl.ie/id/eprint/4020

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