Maintainability | · Dashboard modifiability: Ease with which existing dashboards can be modified. · Data source integration flexibility: Ease of adding new data sources to the BI system. · Visualization library extensibility: Ease with which new visualization types can be added. · Metadata management simplicity: Effort required to maintain and update metadata that describes datasets, reports, or visualizations. · Automated error detection: The ability of the system to automatically detect and, if possible, correct errors in data or computations. · Version control: Mechanisms in place for versioning reports, dashboards, and data models. |
Portability | · Export format diversity: Number of formats (e.g., CSV, PDF, Excel) in which reports can be exported. · Cross-platform compatibility: Number of platforms (e.g., mobile, web) on which BI tools are accessible and functional. · Cloud readiness: Ability of the BI component to operate and scale on cloud platforms. · Mobile responsiveness: Quality of BI dashboards and reports on mobile devices in terms of layout, interaction, and load time. · BI tool migration capabilities: Ease with which BI content (like reports, dashboards) can be migrated to another tool or platform. · Offline access: Capability to access certain BI features or content offline. |
Performance | · Real-time processing: Latency between data ingestion and its availability in BI reports. · Concurrent user handling: Number of simultaneous users the system can support without significant performance degradation. · Background task speed: Speed at which background tasks (like data refreshes or scheduled report runs) are completed. · Aggregation speed: Time taken to aggregate or roll-up data at different levels. · Large dataset handling: Performance consistency when handling exceptionally large datasets. · Resource optimization: Efficiency in using computational resources like CPU, memory, and storage. |
Interoperability | · Third-party tool integration: Number and types of third-party tools (e.g., CRM, ERP) that can be integrated with the BI component. · API availability: Availability and completeness of APIs for external system interactions. · Data connector extensibility: Flexibility in adding connectors to new, unsupported data sources. · Embedding capabilities: Ability to embed BI reports or visualizations in other applications or platforms. · Third-party visualization support: Ability to integrate or use visualization components from third parties. · Open standards adherence: Adherence to open standards for data connectivity, visualization, etc., promoting interoperability. |
Compliance | · Data governance adherence: Compliance of the BI tool with organizational data governance policies. · Regulatory compliance support: Features that assist in complying with relevant data-related regulations (like GDPR or HIPAA). |
Scalability | · Cluster scalability: How well the system scales out by adding more nodes or servers to a cluster. · Data growth adaptability: Performance consistency as the underlying data grows over time. |
Customisability | · Plug-in or extension support: Ability for developers to add custom functionalities or integrations. · User-defined function support: Capability for users to define their own functions for specific computations. |