The information that flows from BI, analytics, and data warehousing systems can help organizations find the right decision-making balance that avoids the extremes of rigid snap decisions and processes. This new survey-based research report examines benefits, barriers, technology solutions, and recommendations for achieving greater agility with business intelligence.By David StodderJanuary 4, 2013
Faster decision cycles, competitive pressures to seize fleeting opportunities, and the continuing need to adjust to upheavals in an interconnected global economy are driving demand for business intelligence and analytics that better support business agility. Organizations need flexibility; yet, even as some organizational structures are shifting to support fluid decision making and faster response to changing conditions, the BI systems that deliver vital data and provide the raw material for analytics are not keeping up.
Whether they are part of IT or business functions, which professionals responsible for designing, developing, and deploying BI, analytics and data warehousing (DW) systems are feeling the heat. Applications that merely give users one report after another are not adequate for agility. Professionals must shift development and deployment approaches so that systems are responsive to business needs and agile oriented toward providing self-service functionality to free users from dependence on IT. Self-service BI, however, must be part of a balance; data professionals must balance user freedom with data governance and the need for stable performance for all users.
This TDWI Best Practices Report focuses on how organizations can achieve greater agility with BI, DW, and analytics through adjustments in technology and development strategies. The report provides analysis of an in-depth research survey and user stories to reveal current strategies and future plans for achieving higher agility. The report offers recommendations for making flexibility, shorter time to value, and self-directed functionality higher priorities in BI, DW, and analytics.
Many leading organizations are implementing agile software development methods for BI, DW, and data integration systems. These methods form an alternative to traditional "waterfall" methods and cycles. Agile methods aim at closer collaboration between users and developers; they proposed iterative cycles to deliver value incrementally rather than only at the end of full waterfall cycles. This report discusses agile method adoption.
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