A data analysis system organizes workflows that prepare data, generate insights, create visualizations, and support decisions. When generative AI is integrated, define its job clearly rather than treating it as an all-purpose solution. section 1.3.6
Judge the system with explicit performance questions:
- How quickly does it begin displaying results (latency), and how long does the complete task take (response time)? section 7.1
- How much data can it process or transfer, and how many queries can it handle concurrently? section 7.1
- Can it remain available and maintain performance as data sources, query complexity, or users increase? section 7.1
Choosing a performance yardstick
A system optimized for quick responses may need a different target from one optimized for accuracy or multiple simultaneous users. Define the important characteristics, establish baselines, and decide whether normal future growth belongs in the target. section 7.1
Reliable operation also depends on compatible data formats, clear prompts, usage and cost monitoring, and handling timeouts or rate-limit errors. Verify generated outputs before preserving prompt patterns for reuse. section 1.3.6
