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Adapting Agile Practices for Data Warehousing, Business Intelligence, and Analytics

Dinesh Batra

Source Title: Journal of Database Management (JDM)28(4)

ISSN: 1063-8016|EISSN: 1533-8010|EISBN13: 9781522510949|DOI: 10.4018/JDM.2017100101

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MLA

Batra, Dinesh. "Adapting Agile Practices for Data Warehousing, Business Intelligence, and Analytics." JDM vol.28, no.4 2017: pp.1-23. http://doi.org/10.4018/JDM.2017100101

APA

Batra, D. (2017). Adapting Agile Practices for Data Warehousing, Business Intelligence, and Analytics. Journal of Database Management (JDM), 28(4), 1-23. http://doi.org/10.4018/JDM.2017100101

Chicago

Batra, Dinesh. "Adapting Agile Practices for Data Warehousing, Business Intelligence, and Analytics," Journal of Database Management (JDM) 28, no.4: 1-23. http://doi.org/10.4018/JDM.2017100101

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Abstract

Business surveys indicate that fewer than 30% of data warehousing and business intelligence (DW/BI) projects meet the stated goals of the budget, schedule, and quality. Agile methods have been suggested as a possible solution, but because of the large size of the typical DW/BI project, it may be difficult to apply the agile values and principles. In this article, the following research questions are raised: Can agile practices be adapted for DW/BI development? What factors influence agile DW/BI development? Six semi-structured interviews were conducted using a questionnaire. The interview transcripts were coded using the grounded theory approach. Eight categories emerged from the analysis: business value, project management, agile development, shared understanding, technological capability, top management commitment, complexity, and organizational culture. Based on the categories, a research framework is proposed. The findings reveal that agile methods are suited for only certain aspects of DW/BI projects and need to be augmented with project management practices.

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Adapting Agile Practices for Data Warehousing, Business Intelligence, and Analytics

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