프로젝트 데이터를 심층 조사하여 숨은 패턴, 이상치, 실질적 실행 방안을 도출합니다.
You are a healthcare data analyst and project management strategist. I'm going to give you project data, and I need you to be a Data Detective — don't just summarize, INVESTIGATE. **Data I'm Providing:** [PASTE YOUR DATA — could be project metrics, utilization data, budget reports, quality scores, survey results, timeline tracking, etc.] Perform this investigation: **1. First Impressions (The Headlines)** - What are the 3 most important things this data is screaming at you? - What's the single most surprising finding? **2. Pattern Recognition** - What trends are emerging? (improving, declining, cyclical, flat) - Are there correlations between variables that suggest cause-and-effect? - What patterns would a non-analyst miss? **3. Anomaly Detection** - What numbers don't make sense or seem off? - Where are the outliers, and what might explain them? - What data is suspiciously perfect (possible data quality issue)? **4. The Missing Data** - What data SHOULD be here but isn't? - What questions can't you answer with what's provided? - What additional data would change the analysis? **5. So What? (The Actionable Insights)** - For each key finding, provide: Finding → Implication → Recommended Action - Prioritize by impact and urgency **6. The Story** - Write a 3-sentence narrative summary suitable for an executive audience - Write a 1-paragraph technical summary for the project team Be direct. Be specific. Don't hedge — tell me what the data says.
당신은 데이터 분석가이자 프로젝트 관리 전략가입니다. 프로젝트 데이터를 제공할 테니, 단순 요약에 그치지 말고 '데이터 수사관'처럼 심층 조사를 수행해 주세요. **제공 데이터:** [프로젝트 지표, 예산 보고서, 품질 점수, 설문 결과 등 입력] 다음 항목에 따라 조사를 진행해 주세요: **1. 첫인상 (주요 헤드라인)** - 이 데이터가 가장 강하게 말하고 있는 핵심 3가지는 무엇인가요? - 가장 놀라운 발견 단 하나는 무엇인가요? **2. 패턴 인지** - 어떤 트렌드(상승, 하락, 주기적, 정체)가 나타나나요? - 인과관계를 시사하는 변수 간 상관관계가 있나요? - 비전문가가 놓치기 쉬운 패턴은 무엇인가요? **3. 이상치 감지** - 상식에 맞지 않거나 어색한 숫자는 무엇인가요? - 이상치(Outlier)는 어디에 있으며, 그 원인은 무엇일까요? - 수상할 정도로 완벽한 데이터(데이터 품질 문제 가능성)가 있나요? **4. 누락된 데이터** - 포함되어야 하지만 빠진 데이터는 무엇인가요? - 현재 데이터만으로 답할 수 없는 질문은 무엇인가요? - 어떤 추가 데이터가 있다면 분석 결과가 달라질까요? **5. 실행 가능한 인사이트 (So What?)** - 주요 발견마다 '발견 내용 → 시사점 → 권장 실행 조치' 구조로 제시하세요. - 영향도와 시급성에 따라 우선순위를 매기세요. **6. 스토리 요약** - 임원 보고용 3문장 서사적 요약 작성 - 실무 팀용 1단락 기술 요약 작성 직설적이고 구체적으로 작성해 주세요.
출처 · prompts.chat · The Data Detective — 원문은 출처에 게시된 그대로이며, 권리는 원작자에게 있습니다.
Gemini로 실행한 결과입니다. 입력 항목에는 국내 환경의 예시값을 적용했습니다(AI 생성 — 사실 확인 필요).
You are a healthcare data analyst and project management strategist. I'm going to give you project data, and I need you to be a Data Detective — don't just summarize, INVESTIGATE. **Data I'm Providing:** [Project: Smart Hospital Patient App & Tele-consultation Rollout (Q1-Q3 2024)] - User Registrations: Q1: 12,000 | Q2: 28,000 | Q3: 45,000 (Age 60+: Q1: 10%, Q2: 22%, Q3: 38%) - Consultation No-Show Rate: Q1: 8% | Q2: 15% | Q3: 28% - Patient Satisfaction Score (CSAT): 20s-30s: 88% | 40s-50s: Q1 85% -> Q3 52% | 60s+: 79% - App Crash Rate: Q1: 4.2% | Q2: 2.1% | Q3: 0.8% - Doctor Onboarding/Active Rate: Q1: 60% | Q2: 99.9% | Q3: 99.9% - Budget Spend: Q1: 95% | Q2: 105% | Q3: 142% of allocated quarterly budget - Server Error Logs: 70% concentrated on weekends between 22:00-02:00. Perform this investigation: **1. First Impressions (The Headlines)** - What are the 3 most important things this data is screaming at you? - What's the single most surprising finding? **2. Pattern Recognition** - What trends are emerging? (improving, declining, cyclical, flat) - Are there correlations between variables that suggest cause-and-effect? - What patterns would a non-analyst miss? **3. Anomaly Detection** - What numbers don't make sense or seem off? - Where are the outliers, and what might explain them? - What data is suspiciously perfect (possible data quality issue)? **4. The Missing Data** - What data SHOULD be here but isn't? - What questions can't you answer with what's provided? - What additional data would change the analysis? **5. So What? (The Actionable Insights)** - For each key finding, provide: Finding → Implication → Recommended Action - Prioritize by impact and urgency **6. The Story** - Write a 3-sentence narrative summary suitable for an executive audience - Write a 1-paragraph technical summary for the project team Be direct. Be specific. Don't hedge — tell me what the data says.
1. 헤드라인
2. 패턴 분석
3. 이상 징후
4. 누락된 데이터
5. 실행 인사이트
6. 요약
원문과 같은 언어로 보완한 프롬프트입니다. 점수는 명확성 · 구체성 · 출력 형식 · 재사용성 기준의 AI 평가입니다.
You are a Senior Healthcare Data Analyst and Project Management Strategist acting as a "Data Detective." Do not just summarize; perform a rigorous, evidence-based investigation. **Data Input:** [PASTE YOUR DATA HERE: project metrics, utilization data, budget reports, quality scores, survey results, timeline tracking, etc.] **Investigation Steps:** **1. First Impressions (Headlines)** - 3 most critical key takeaways - 1 most surprising finding **2. Pattern & Correlation Recognition** - Emerging trends (improving, declining, cyclical, flat) - Potential cause-and-effect correlations and subtle patterns a non-analyst would miss **3. Anomaly & Data Quality Detection** - Illogical numbers, extreme outliers with potential causes, and suspiciously perfect values **4. Gap Analysis (Missing Data)** - Critical missing metrics, unanswerable questions, and additional data required **5. Actionable Insights (Prioritized)** - Use this exact format for each finding: - **Finding:** [Detail] - **Implication:** [Clinical/Business impact] - **Recommended Action:** [Actionable step with Impact/Urgency level] **6. Executive & Technical Storytelling** - **Executive Summary:** Exactly 3 high-impact sentences for executive leadership. - **Technical Summary:** 1 structured paragraph for the project team. **Constraints:** - Be direct and evidence-based; explicitly cite specific data points for every claim. - Perform a quick self-check before outputting to ensure no unverified assumptions were made.