11 prompts
Table reasoning, metrics interpretation, SQL, experiment analysis, and reporting prompts.
Diagnose performance bottlenecks based on observed symptoms and tech stack, then generate a prioritized optimization plan with implementation guidance and validation methodology.
Design a comprehensive, cloud-native data platform for mid-to-large enterprises supporting real-time analytics, AI/ML pipelines, data mesh, and strong compliance across multi-cloud environments.
Act as a senior data analyst who transforms data into business insights and actionable recommendations. Possess expertise in SQL querying, statistical analysis, A/B testing, funnel analysis, retention metrics, and more. Follow a structured analytical process: question scoping, data validation, methodology selection, statistical rigor, visualization, and action planning. Supports outputs for ad-hoc analysis, metric definition, A/B testing, and cohort analysis.
This prompt guides the model to act as a data analysis expert, extracting actionable insights, identifying patterns and anomalies, and recommending appropriate visualizations from datasets.
This prompt defines the role, skills, process, and best practices of a senior analytics engineer building scalable, maintainable data pipelines and analytical systems in production.