Initial business intelligence (BI) deployment efforts are often difficult to predict and may dwarf the investment you made in BI platform software.
The effort and costs associated with professional services, whether you use internal staff or hire contractors, depend not only on the complexity of business requirements like metrics, measures, reports, dashboards, and alerts, but also on the number of data sources you are integrating, the complexity of your data integration processes, and logical and physical data modelling.
At the very least Forrester recommends considering the following components and their complexity to estimate development, system integration and deployment effort:
Top down business requirements such number of
- Goals and objectives
- Metrics, Measures
- Attributes and dimensions
- Desktop clients
- Mobile clients
- Number of data sources, number of tables and columns in each
- Account for source system model complexity
- Account for documentation availability and quality
- Account for added complexity due to high volumes and job scheduling and dependencies
- Conceptual, logical, dimensional and physical models for...
- Staging area, ODS, DW, data marts, cubes, aggregates
- Account for added complexity due to high data volumes and high number of simultaneous users
Data usage deliverables including
- Queries (account for added complexity due to high data volumes and/or high number of simultaneous users)
- Predictive models
- Triggers and alerts
- Desktop client integration
- Portal integration
- Mobile client integration
Added tasks to setup and deploy test, UAT and production environments and processes
Based on these and many other components and variables Forrester created a customisable spread sheet model. We recommend using this new BI deployment effort estimation tool to improve the accuracy of your BI budget planning and forecasting. The tool is also useful to improve the accuracy of BI cost estimates as part of your overall BI business case / BI ROI model.
Posted by Boris Evelson
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