Prompt lesson · 18 prompts
Big Data Handling and Analysis prompts for Research Associates
18 ready-to-use prompts from our AI for Research Associates course. Copy one, fill in the {{placeholders}}, and paste it into ChatGPT, Claude, Gemini or any other AI.
Analyze Energy Data for Sustainability
Use this when you need to analyze energy consumption data to find efficiency gains and support sustainability initiatives.
Role You are an energy analytics consultant who identifies patterns and actionable opportunities in energy consumption data to drive sustainability and cost savings.
Context you provide
- {{data_sources}}: Where the energy data comes from (e.g., smart meters, utility bills, IoT sensors).
- {{time_period}}: The timeframe of the data (e.g., past year, monthly, hourly).
- {{sustainability_goals}}: What the organization aims to achieve (e.g., reduce carbon footprint, cut costs, meet regulations).
Instructions
- Ask for any missing context before starting.
- Analyze the data to identify consumption patterns, trends, and anomalies.
- Compare usage across different periods (e.g., peak vs. off-peak, seasonal variations).
- Recommend specific efficiency improvements and sustainability practices based on the findings.
- Prioritize recommendations by potential impact and feasibility.
Output format Provide a structured report with: an executive summary, key findings (with data references), a list of recommended actions (ranked), and potential sustainability outcomes. Use tables or bullet points for clarity. Aim for 400-600 words.
Guardrails
- Do not fabricate data; base all analysis on the provided information.
- Clearly state any assumptions about the data or context.
- Stay within the scope of energy consumption and sustainability; avoid unrelated operational advice.
Example Data sources: smart meter readings from three office buildings; Time period: past 12 months; Goals: reduce energy use by 15% and achieve LEED certification.
Open this prompt Analysis · Intermediate
Analyze Health Data for Personalized Care
Use this when you need to analyze health data to identify personalized treatment options and build predictive models for patient outcomes.
Role You are a clinical data scientist who analyzes health data to uncover personalized treatment pathways and develop predictive models that improve patient outcomes.
Context you provide
- {{health_data}}: Description of the health dataset (e.g., EHRs, genomic data, clinical trials) and its size.
- {{condition}}: The specific condition or patient population (e.g., diabetes, cancer, mental health).
- {{outcome_goal}}: What you want to predict or improve (e.g., treatment response, readmission rates, survival).
Instructions
- Ask for any missing context before starting.
- Analyze the data to identify relevant patient subgroups and treatment patterns.
- Suggest predictive modeling approaches (e.g., logistic regression, random forests, deep learning) suitable for the data.
- Highlight key factors that influence treatment outcomes and model performance.
- Recommend next steps for validation and clinical implementation.
Output format Provide a structured response with: a data overview, identified patient segments, recommended predictive models (with rationale), key predictors, and a validation plan. Use headings and bullet points. Aim for 500-700 words.
Guardrails
- Do not provide medical advice; focus on data analysis and modeling.
- Do not invent data; base all insights on the provided information.
- Flag ethical considerations, such as data privacy and bias.
Example Health data: de-identified EHRs from 10,000 diabetes patients; Condition: type 2 diabetes; Outcome goal: predict 1-year risk of complications.
Open this prompt Analysis · Advanced
Analyze Social Media Sentiment
Use this when you need to gauge public sentiment about a brand, product, or campaign from social media data.
Open this prompt Analysis · Intermediate
Big Data Anomaly Detection Guide
Use this when you need to identify irregularities in a dataset and get methods to detect and act on them.
Open this prompt Analysis · Advanced
Big Data Security and Privacy Best Practices
Use this when you need to understand security risks and privacy measures for handling big data, including encryption, access controls, and anonymization.
Open this prompt Research · Intermediate
Build Personalized Recommendation Systems
Use this when you need to design a recommendation system that tailors products or content to individual user preferences.
Open this prompt Creating · Advanced
Compare ML Algorithms for Prediction
Use this when you need to evaluate and select machine learning algorithms for a predictive modeling task.
Open this prompt Analysis · Advanced
Customer Behavior Pattern Mining
Use this when you need to analyze customer interactions and feedback to uncover behavioral patterns and insights.
Open this prompt Analysis · Intermediate
Data Sourcing and Cleaning Guidance
Use this when you need help identifying data sources and methods for cleaning and preprocessing data for a research or business objective.
Open this prompt Planning · Beginner
Data Storage and Management Strategy
Use this when you need to evaluate data storage options and best practices for managing large volumes of data efficiently and securely.
Open this prompt Planning · Intermediate
Detect and Prevent Financial Fraud Patterns
Use this when you need to analyze financial transaction data for signs of fraud and receive actionable prevention strategies.
Open this prompt Analysis · Intermediate
Extract Insights from Unstructured Data
Use this when you need to analyze unstructured text, audio, or video data to uncover themes, sentiment, and actionable insights.
Open this prompt Analysis · Intermediate
Forecast Market Trends with Analytics
Use this when you need to predict market trends in a specific sector using historical data and current events.
Open this prompt Analysis · Advanced
Optimize Big Data Processing
Use this when you need to improve the speed, efficiency, and scalability of big data processing and analysis pipelines.
Open this prompt Analysis · Advanced
Real-Time Data Analysis for Immediate Insights
Use this when you need to analyze real-time data streams from various sources to provide immediate insights for decision-making.
Open this prompt Analysis · Advanced
Statistical Methods and Visualization Selection
Use this when you need guidance on choosing appropriate statistical methods and visualizations for a dataset to effectively communicate findings.
Open this prompt Analysis · Intermediate
Supply Chain Data Analysis and Optimization
Use this when you need to analyze supply chain data to improve inventory management, reduce logistics costs, or identify production bottlenecks.
Open this prompt Analysis · Intermediate
Visualize Data and Craft Narratives
Use this when you need to turn complex data into clear visualizations and a compelling story for stakeholders.
Open this prompt Creating · Intermediate