Results for “data”

Estimate TAM, SAM and SOM for [product] in [market/region]. Use a bottom-up approach, state every assumption clearly, show the math, give a range rather than one number, and list which assumptions I should verify with real data.

Create a checklist to make [website/brand] more likely to be cited by AI search tools and chat assistants. Cover clear entity information, structured data, concise answer-first content, original data, authoritative mentions, FAQ formatting and freshness. Prioritise actions for a small team.

Analyze these survey responses and build 3 marketing personas. For each: name, demographics, goals, pains, buying triggers, objections, preferred channels, and 2 real quotes from the data. Note how many respondents fit each persona. Responses: [paste data]

A futuristic holographic interface floating in a dark room: glowing [color] HUD panels, rotating 3D globe, scrolling data and waveforms, light flickers and scan lines. A hand gestures and the panels respond. Cinematic depth of field, subtle haze, high-tech mood.

A clean motion graphics animation showing [data story, e.g. global solar energy growth from 2010 to 2025]: bars rising one by one, numbers counting up, a line chart drawing itself, smooth easing transitions. Flat modern design, [brand colors] on a dark background, minimal and readable.

Teach me [statistics concept, e.g. standard deviation / hypothesis testing] using a small realistic dataset about [topic I care about]. Show the data, calculate step by step, explain what the result means in plain English, and give me a similar dataset to try.

I'm interested in researching [broad topic] for my [degree] thesis in [field]. Help me narrow it down: suggest 5 focused research questions, evaluate each for originality, feasibility and available data, recommend the strongest one, and outline possible methods and key literature to start with.

Help me write a lab report for an experiment on [topic]. Aim: [aim]. Method: [brief steps]. Results: [data]. Write it with sections for Title, Abstract, Introduction, Method, Results (with a suggested table/graph), Discussion (explain trends, sources of error, improvements) and Conclusion. Use formal scientific langua…

Act as a data analyst. Database: [PostgreSQL / BigQuery / Snowflake / MySQL] Tables: [users(id, created_at), events(user_id, event_name, created_at), orders(...)] Questions: [monthly cohort retention, weekly active users, sign-up to purchase funnel] Write the queries with CTEs and comments, explain each step, and desc…

You are a machine learning engineer. Problem: [classification / regression] Data: [columns, target, size] Goal: [what decision the model supports] Write a scikit-learn pipeline: data loading, cleaning, feature engineering, train/test split, a baseline model and a stronger model, cross-validation, appropriate metrics,…

You are an engineer who builds production AI features. Feature idea: [e.g. summarise support tickets, auto-tag products] Stack: [details] Data involved: [types, sensitivity] Design: the prompt and system instructions, input/output format (JSON schema), handling of errors and timeouts, cost and latency considerations,…

Act as a cloud infrastructure engineer. Cloud: [AWS / GCP / Azure] Resources needed: [e.g. VPC, database, container service, storage bucket] Environments: [details] Write Terraform with a sensible module structure, variables and outputs, remote state configuration, tagging, and comments. Explain the plan/apply workflo…